CINXE.COM

Search results for: empirical models

<!DOCTYPE html> <html lang="en" dir="ltr"> <head> <!-- Google tag (gtag.js) --> <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script> <!-- Yandex.Metrika counter --> <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript> <!-- /Yandex.Metrika counter --> <!-- Matomo --> <!-- End Matomo Code --> <title>Search results for: empirical models</title> <meta name="description" content="Search results for: empirical models"> <meta name="keywords" content="empirical models"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="empirical models" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="empirical models"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 8943</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: empirical models</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8943</span> Diagonal Vector Autoregressive Models and Their Properties</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Usoro%20Anthony%20E.">Usoro Anthony E.</a>, <a href="https://publications.waset.org/abstracts/search?q=Udoh%20Emediong"> Udoh Emediong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diagonal Vector Autoregressive Models are special classes of the general vector autoregressive models identified under certain conditions, where parameters are restricted to the diagonal elements in the coefficient matrices. Variance, autocovariance, and autocorrelation properties of the upper and lower diagonal VAR models are derived. The new set of VAR models is verified with empirical data and is found to perform favourably with the general VAR models. The advantage of the diagonal models over the existing models is that the new models are parsimonious, given the reduction in the interactive coefficients of the general VAR models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=VAR%20models" title="VAR models">VAR models</a>, <a href="https://publications.waset.org/abstracts/search?q=diagonal%20VAR%20models" title=" diagonal VAR models"> diagonal VAR models</a>, <a href="https://publications.waset.org/abstracts/search?q=variance" title=" variance"> variance</a>, <a href="https://publications.waset.org/abstracts/search?q=autocovariance" title=" autocovariance"> autocovariance</a>, <a href="https://publications.waset.org/abstracts/search?q=autocorrelations" title=" autocorrelations"> autocorrelations</a> </p> <a href="https://publications.waset.org/abstracts/157980/diagonal-vector-autoregressive-models-and-their-properties" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157980.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">116</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8942</span> A Review on Water Models of Surface Water Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shahbaz%20G.%20Hassan">Shahbaz G. Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=empirical%20models" title="empirical models">empirical models</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical" title=" mathematical"> mathematical</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical" title=" statistical"> statistical</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20quality" title=" water quality"> water quality</a> </p> <a href="https://publications.waset.org/abstracts/60966/a-review-on-water-models-of-surface-water-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60966.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">264</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8941</span> Empirical Model for the Estimation of Global Solar Radiation on Horizontal Surface in Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Malika%20Fekih">Malika Fekih</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdenour%20Bourabaa"> Abdenour Bourabaa</a>, <a href="https://publications.waset.org/abstracts/search?q=Rafika%20Hariti"> Rafika Hariti</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Saighi"> Mohamed Saighi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20solar%20radiation" title="global solar radiation">global solar radiation</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20model" title=" empirical model"> empirical model</a>, <a href="https://publications.waset.org/abstracts/search?q=semi%20arid%20areas" title=" semi arid areas"> semi arid areas</a>, <a href="https://publications.waset.org/abstracts/search?q=climatological%20parameters" title=" climatological parameters"> climatological parameters</a> </p> <a href="https://publications.waset.org/abstracts/17957/empirical-model-for-the-estimation-of-global-solar-radiation-on-horizontal-surface-in-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17957.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">502</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8940</span> Empirical Modeling of Air Dried Rubberwood Drying System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Khamtree">S. Khamtree</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Ratanawilai"> T. Ratanawilai</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Nuntadusit"> C. Nuntadusit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 &deg;C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (<em>R&sup2;</em>), Root Mean Square Error (RMSE) and Chi-square (&chi;&sup2;) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (<em>R&sup2; </em>= 0.9963<strong>)</strong> for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=empirical%20models" title="empirical models">empirical models</a>, <a href="https://publications.waset.org/abstracts/search?q=rubberwood" title=" rubberwood"> rubberwood</a>, <a href="https://publications.waset.org/abstracts/search?q=moisture%20ratio" title=" moisture ratio"> moisture ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=hot%20air%20drying" title=" hot air drying"> hot air drying</a> </p> <a href="https://publications.waset.org/abstracts/93645/empirical-modeling-of-air-dried-rubberwood-drying-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93645.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">267</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8939</span> Public Spending and Economic Growth: An Empirical Analysis of Developed Countries</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bernur%20Acikgoz">Bernur Acikgoz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to investigate the effects of public spending on economic growth and examine the sources of economic growth in developed countries since the 1990s. This paper analyses whether public spending effect on economic growth based on Cobb-Douglas Production Function with the two econometric models with Autoregressive Distributed Lag (ARDL) and Dynamic Fixed Effect (DFE) for 21 developed countries (high-income OECD countries), over the period 1990-2013. Our models results are parallel to each other and the models support that public spending has an important role for economic growth. This result is accurate with theories and previous empirical studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=public%20spending" title="public spending">public spending</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20growth" title=" economic growth"> economic growth</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data" title=" panel data"> panel data</a>, <a href="https://publications.waset.org/abstracts/search?q=ARDL%20models" title=" ARDL models"> ARDL models</a> </p> <a href="https://publications.waset.org/abstracts/49809/public-spending-and-economic-growth-an-empirical-analysis-of-developed-countries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">370</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8938</span> The Promotion Effects for a Supply Chain System with a Dominant Retailer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tai-Yue%20Wang">Tai-Yue Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yi-Ho%20Chen"> Yi-Ho Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=supply%20chain" title="supply chain">supply chain</a>, <a href="https://publications.waset.org/abstracts/search?q=price%20promotion" title=" price promotion"> price promotion</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20models" title=" mathematical models"> mathematical models</a>, <a href="https://publications.waset.org/abstracts/search?q=dominant%20retailer" title=" dominant retailer"> dominant retailer</a> </p> <a href="https://publications.waset.org/abstracts/40876/the-promotion-effects-for-a-supply-chain-system-with-a-dominant-retailer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40876.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">401</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8937</span> Hydrological Modeling of Watersheds Using the Only Corresponding Competitor Method: The Case of M’Zab Basin, South East Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oulad%20Naoui%20Noureddine">Oulad Naoui Noureddine</a>, <a href="https://publications.waset.org/abstracts/search?q=Cherif%20ELAmine"> Cherif ELAmine</a>, <a href="https://publications.waset.org/abstracts/search?q=Djehiche%20Abdelkader"> Djehiche Abdelkader</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world.&nbsp; In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M&rsquo;ZAB&nbsp;&nbsp; Watershed (South East of Algeria) to adapt a few empirical models for any hydrological regime.&nbsp; The results obtained allow to authorize a certain number of visions, in which it would be interesting to experiment with hydrological models that improve collectively or separately the data of a catchment by the OCC method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=modelling" title="modelling">modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall-runoff%20relationship" title=" rainfall-runoff relationship"> rainfall-runoff relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20model" title=" empirical model"> empirical model</a>, <a href="https://publications.waset.org/abstracts/search?q=OCC" title=" OCC"> OCC</a> </p> <a href="https://publications.waset.org/abstracts/70690/hydrological-modeling-of-watersheds-using-the-only-corresponding-competitor-method-the-case-of-mzab-basin-south-east-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70690.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">265</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8936</span> Modelling the Dynamics of Corporate Bonds Spreads with Asymmetric GARCH Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S%C3%A9lima%20Baccar">Sélima Baccar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ephraim%20Clark"> Ephraim Clark</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper can be considered as a new perspective to analyse credit spreads. A comprehensive empirical analysis of conditional variance of credit spreads indices is performed using various GARCH models. Based on a comparison between traditional and asymmetric GARCH models with alternative functional forms of the conditional density, we intend to identify what macroeconomic and financial factors have driven daily changes in the US Dollar credit spreads in the period from January 2011 through January 2013. The results provide a strong interdependence between credit spreads and the explanatory factors related to the conditions of interest rates, the state of the stock market, the bond market liquidity and the exchange risk. The empirical findings support the use of asymmetric GARCH models. The AGARCH and GJR models outperform the traditional GARCH in credit spreads modelling. We show, also, that the leptokurtic Student-t assumption is better than the Gaussian distribution and improves the quality of the estimates, whatever the rating or maturity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corporate%20bonds" title="corporate bonds">corporate bonds</a>, <a href="https://publications.waset.org/abstracts/search?q=default%20risk" title=" default risk"> default risk</a>, <a href="https://publications.waset.org/abstracts/search?q=credit%20spreads" title=" credit spreads"> credit spreads</a>, <a href="https://publications.waset.org/abstracts/search?q=asymmetric%20garch%20models" title=" asymmetric garch models"> asymmetric garch models</a>, <a href="https://publications.waset.org/abstracts/search?q=student-t%20distribution" title=" student-t distribution"> student-t distribution</a> </p> <a href="https://publications.waset.org/abstracts/2699/modelling-the-dynamics-of-corporate-bonds-spreads-with-asymmetric-garch-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2699.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8935</span> Empirical Roughness Progression Models of Heavy Duty Rural Pavements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nahla%20H.%20Alaswadko">Nahla H. Alaswadko</a>, <a href="https://publications.waset.org/abstracts/search?q=Rayya%20A.%20Hassan"> Rayya A. Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayar%20N.%20Mohammed"> Bayar N. Mohammed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=roughness%20progression" title="roughness progression">roughness progression</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20model" title=" empirical model"> empirical model</a>, <a href="https://publications.waset.org/abstracts/search?q=pavement%20performance" title=" pavement performance"> pavement performance</a>, <a href="https://publications.waset.org/abstracts/search?q=heavy%20duty%20pavement" title=" heavy duty pavement"> heavy duty pavement</a> </p> <a href="https://publications.waset.org/abstracts/81268/empirical-roughness-progression-models-of-heavy-duty-rural-pavements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81268.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8934</span> Modeling of Daily Global Solar Radiation Using Ann Techniques: A Case of Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Benkaciali">Said Benkaciali</a>, <a href="https://publications.waset.org/abstracts/search?q=Mourad%20Haddadi"> Mourad Haddadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdallah%20Khellaf"> Abdallah Khellaf</a>, <a href="https://publications.waset.org/abstracts/search?q=Kacem%20Gairaa"> Kacem Gairaa</a>, <a href="https://publications.waset.org/abstracts/search?q=Mawloud%20Guermoui"> Mawloud Guermoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=empirical%20models" title="empirical models">empirical models</a>, <a href="https://publications.waset.org/abstracts/search?q=multilayer%20perceptron%20neural%20network" title=" multilayer perceptron neural network"> multilayer perceptron neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=solar%20radiation" title=" solar radiation"> solar radiation</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20formulas" title=" statistical formulas"> statistical formulas</a> </p> <a href="https://publications.waset.org/abstracts/60646/modeling-of-daily-global-solar-radiation-using-ann-techniques-a-case-of-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60646.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">345</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8933</span> Comprehensive Experimental Study to Determine Energy Dissipation of Nappe Flows on Stepped Chutes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdollah%20Ghasempour">Abdollah Ghasempour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Reza%20Kavianpour"> Mohammad Reza Kavianpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Galoie"> Majid Galoie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study has investigated the fundamental parameters which have effective role on energy dissipation of nappe flows on stepped chutes in order to estimate an empirical relationship using dimensional analysis. To gain this goal, comprehensive experimental study on some large-scale physical models with various step geometries, slopes, discharges, etc. were carried out. For all models, hydraulic parameters such as velocity, pressure, water depth, flow regime and etc. were measured precisely. The effective parameters, then, could be determined by analysis of experimental data. Finally, a dimensional analysis was done in order to estimate an empirical relationship for evaluation of energy dissipation of nappe flows on stepped chutes. Because of using the large-scale physical models in this study, the empirical relationship is in very good agreement with the experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nappe%20flow" title="nappe flow">nappe flow</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20dissipation" title=" energy dissipation"> energy dissipation</a>, <a href="https://publications.waset.org/abstracts/search?q=stepped%20chute" title=" stepped chute"> stepped chute</a>, <a href="https://publications.waset.org/abstracts/search?q=dimensional%20analysis" title=" dimensional analysis "> dimensional analysis </a> </p> <a href="https://publications.waset.org/abstracts/20115/comprehensive-experimental-study-to-determine-energy-dissipation-of-nappe-flows-on-stepped-chutes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20115.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">361</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8932</span> Comparison of Applicability of Time Series Forecasting Models VAR, ARCH and ARMA in Management Science: Study Based on Empirical Analysis of Time Series Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Tariq">Muhammad Tariq</a>, <a href="https://publications.waset.org/abstracts/search?q=Hammad%20Tahir"> Hammad Tahir</a>, <a href="https://publications.waset.org/abstracts/search?q=Fawwad%20Mahmood%20Butt"> Fawwad Mahmood Butt </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=forecasting" title="forecasting">forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=auto%20regression" title=" auto regression"> auto regression</a>, <a href="https://publications.waset.org/abstracts/search?q=ARCH" title=" ARCH"> ARCH</a>, <a href="https://publications.waset.org/abstracts/search?q=ARMA" title=" ARMA"> ARMA</a> </p> <a href="https://publications.waset.org/abstracts/45124/comparison-of-applicability-of-time-series-forecasting-models-var-arch-and-arma-in-management-science-study-based-on-empirical-analysis-of-time-series-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45124.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">348</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8931</span> Kou Jump Diffusion Model: An Application to the SP 500; Nasdaq 100 and Russell 2000 Index Options</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wajih%20Abbassi">Wajih Abbassi</a>, <a href="https://publications.waset.org/abstracts/search?q=Zouhaier%20Ben%20Khelifa"> Zouhaier Ben Khelifa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=jump-diffusion%20process" title="jump-diffusion process">jump-diffusion process</a>, <a href="https://publications.waset.org/abstracts/search?q=Kou%20model" title=" Kou model"> Kou model</a>, <a href="https://publications.waset.org/abstracts/search?q=Leptokurtic%20feature" title=" Leptokurtic feature"> Leptokurtic feature</a>, <a href="https://publications.waset.org/abstracts/search?q=trust-region-reflective%20algorithm" title=" trust-region-reflective algorithm"> trust-region-reflective algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=US%20index%20options" title=" US index options"> US index options</a> </p> <a href="https://publications.waset.org/abstracts/17915/kou-jump-diffusion-model-an-application-to-the-sp-500-nasdaq-100-and-russell-2000-index-options" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17915.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">429</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8930</span> Dynamic Modeling of the Exchange Rate in Tunisia: Theoretical and Empirical Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chokri%20Slim">Chokri Slim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stationarity" title="stationarity">stationarity</a>, <a href="https://publications.waset.org/abstracts/search?q=cointegration" title=" cointegration"> cointegration</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20models" title=" dynamic models"> dynamic models</a>, <a href="https://publications.waset.org/abstracts/search?q=causality" title=" causality"> causality</a>, <a href="https://publications.waset.org/abstracts/search?q=VECM%20models" title=" VECM models"> VECM models</a> </p> <a href="https://publications.waset.org/abstracts/34415/dynamic-modeling-of-the-exchange-rate-in-tunisia-theoretical-and-empirical-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34415.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">364</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8929</span> Superiority of High Frequency Based Volatility Models: Empirical Evidence from an Emerging Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sibel%20Celik">Sibel Celik</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%BCseyin%20Ergin"> Hüseyin Ergin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volatility" title="volatility">volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH%20model" title=" GARCH model"> GARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=realized%20volatility" title=" realized volatility"> realized volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20frequency%20data" title=" high frequency data"> high frequency data</a> </p> <a href="https://publications.waset.org/abstracts/18459/superiority-of-high-frequency-based-volatility-models-empirical-evidence-from-an-emerging-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18459.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">486</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8928</span> Markov Switching of Conditional Variance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Josip%20Arneric">Josip Arneric</a>, <a href="https://publications.waset.org/abstracts/search?q=Blanka%20Skrabic%20Peric"> Blanka Skrabic Peric</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emerging%20markets" title="emerging markets">emerging markets</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20switching" title=" Markov switching"> Markov switching</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH%20model" title=" GARCH model"> GARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=transition%20probabilities" title=" transition probabilities"> transition probabilities</a> </p> <a href="https://publications.waset.org/abstracts/23987/markov-switching-of-conditional-variance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23987.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">455</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8927</span> Orthogonal Metal Cutting Simulation of Steel AISI 1045 via Smoothed Particle Hydrodynamic Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Hamed%20Hashemi%20Sohi">Seyed Hamed Hashemi Sohi</a>, <a href="https://publications.waset.org/abstracts/search?q=Gerald%20Jo%20Denoga"> Gerald Jo Denoga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metal%20cutting" title="metal cutting">metal cutting</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothed%20particle%20hydrodynamics" title=" smoothed particle hydrodynamics"> smoothed particle hydrodynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=constitutive%20models" title=" constitutive models"> constitutive models</a>, <a href="https://publications.waset.org/abstracts/search?q=experimental" title=" experimental"> experimental</a>, <a href="https://publications.waset.org/abstracts/search?q=cutting%20forces%20analyses" title=" cutting forces analyses"> cutting forces analyses</a> </p> <a href="https://publications.waset.org/abstracts/70310/orthogonal-metal-cutting-simulation-of-steel-aisi-1045-via-smoothed-particle-hydrodynamic-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70310.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">261</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8926</span> Comparison of Wake Oscillator Models to Predict Vortex-Induced Vibration of Tall Chimneys</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saba%20Rahman">Saba Rahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Arvind%20K.%20Jain"> Arvind K. Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20D.%20Bharti"> S. D. Bharti</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20K.%20Datta"> T. K. Datta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chimney" title="chimney">chimney</a>, <a href="https://publications.waset.org/abstracts/search?q=deterministic%20model" title=" deterministic model"> deterministic model</a>, <a href="https://publications.waset.org/abstracts/search?q=van%20der%20pol" title=" van der pol"> van der pol</a>, <a href="https://publications.waset.org/abstracts/search?q=vortex-induced%20vibration" title=" vortex-induced vibration"> vortex-induced vibration</a> </p> <a href="https://publications.waset.org/abstracts/141523/comparison-of-wake-oscillator-models-to-predict-vortex-induced-vibration-of-tall-chimneys" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141523.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">221</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8925</span> Empirical and Indian Automotive Equity Portfolio Decision Support</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Sankar">P. Sankar</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20James%20Daniel%20Paul"> P. James Daniel Paul</a>, <a href="https://publications.waset.org/abstracts/search?q=Siddhant%20Sahu"> Siddhant Sahu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Indian%20automotive%20sector" title="Indian automotive sector">Indian automotive sector</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market%20decisions" title=" stock market decisions"> stock market decisions</a>, <a href="https://publications.waset.org/abstracts/search?q=equity%20portfolio%20analysis" title=" equity portfolio analysis"> equity portfolio analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree%20classifiers" title=" decision tree classifiers"> decision tree classifiers</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20data%20analysis" title=" statistical data analysis"> statistical data analysis</a> </p> <a href="https://publications.waset.org/abstracts/6454/empirical-and-indian-automotive-equity-portfolio-decision-support" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6454.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">485</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8924</span> Copula Markov Switching Multifractal Models for Forecasting Value-at-Risk </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Giriraj%20Achari">Giriraj Achari</a>, <a href="https://publications.waset.org/abstracts/search?q=Malay%20Bhattacharyya"> Malay Bhattacharyya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Copula" title="Copula">Copula</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20Switching" title=" Markov Switching"> Markov Switching</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractal" title=" multifractal"> multifractal</a>, <a href="https://publications.waset.org/abstracts/search?q=value-at-risk" title=" value-at-risk"> value-at-risk</a> </p> <a href="https://publications.waset.org/abstracts/115727/copula-markov-switching-multifractal-models-for-forecasting-value-at-risk" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115727.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">165</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8923</span> Empirical Evaluation of Gradient-Based Training Algorithms for Ordinary Differential Equation Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martin%20K.%20Steiger">Martin K. Steiger</a>, <a href="https://publications.waset.org/abstracts/search?q=Lukas%20Heisler"> Lukas Heisler</a>, <a href="https://publications.waset.org/abstracts/search?q=Hans-Georg%20Brachtendorf"> Hans-Georg Brachtendorf</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title="deep neural networks">deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=gradient-based%20learning" title=" gradient-based learning"> gradient-based learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=ordinary%20differential%20equation%20networks" title=" ordinary differential equation networks"> ordinary differential equation networks</a> </p> <a href="https://publications.waset.org/abstracts/145435/empirical-evaluation-of-gradient-based-training-algorithms-for-ordinary-differential-equation-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145435.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8922</span> Optimized Text Summarization Model on Mobile Screens for Sight-Interpreters: An Empirical Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jianhua%20Wang">Jianhua Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To obtain key information quickly from long texts on small screens of mobile devices, sight-interpreters need to establish optimized summarization model for fast information retrieval. Four summarization models based on previous studies were studied including title+key words (TKW), title+topic sentences (TTS), key words+topic sentences (KWTS) and title+key words+topic sentences (TKWTS). Psychological experiments were conducted on the four models for three different genres of interpreting texts to establish the optimized summarization model for sight-interpreters. This empirical study shows that the optimized summarization model for sight-interpreters to quickly grasp the key information of the texts they interpret is title+key words (TKW) for cultural texts, title+key words+topic sentences (TKWTS) for economic texts and topic sentences+key words (TSKW) for political texts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=different%20genres" title="different genres">different genres</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20screens" title=" mobile screens"> mobile screens</a>, <a href="https://publications.waset.org/abstracts/search?q=optimized%20summarization%20models" title=" optimized summarization models"> optimized summarization models</a>, <a href="https://publications.waset.org/abstracts/search?q=sight-interpreters" title=" sight-interpreters"> sight-interpreters</a> </p> <a href="https://publications.waset.org/abstracts/57345/optimized-text-summarization-model-on-mobile-screens-for-sight-interpreters-an-empirical-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57345.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">314</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8921</span> Prediction of Trailing-Edge Noise under Adverse-Pressure Gradient Effect</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Chen">Li Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For an aerofoil or hydrofoil in high Reynolds number flows, broadband noise is generated efficiently as the result of the turbulence convecting over the trailing edge. This noise can be related to the surface pressure fluctuations, which can be predicted by either CFD or empirical models. However, in reality, the aerofoil or hydrofoil often operates at an angle of attack. Under this situation, the flow is subjected to an Adverse-Pressure-Gradient (APG), and as a result, a flow separation may occur. This study is to assess trailing-edge noise models for such flows. In the present work, the trailing-edge noise from a 2D airfoil at 6 degree of angle of attach is investigated. Under this condition, the flow is experiencing a strong APG, and the flow separation occurs. The flow over the airfoil with a chord of 300 mm, equivalent to a Reynold Number 4x10⁵, is simulated using RANS with the SST k-ɛ turbulent model. The predicted surface pressure fluctuations are compared with the published experimental data and empirical models, and show a good agreement with the experimental data. The effect of the APG on the trailing edge noise is discussed, and the associated trailing edge noise is calculated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aero-acoustics" title="aero-acoustics">aero-acoustics</a>, <a href="https://publications.waset.org/abstracts/search?q=adverse-pressure%20gradient" title=" adverse-pressure gradient"> adverse-pressure gradient</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20fluid%20dynamics" title=" computational fluid dynamics"> computational fluid dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=trailing-edge%20noise" title=" trailing-edge noise"> trailing-edge noise</a> </p> <a href="https://publications.waset.org/abstracts/65472/prediction-of-trailing-edge-noise-under-adverse-pressure-gradient-effect" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65472.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">336</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8920</span> Heteroscedastic Parametric and Semiparametric Smooth Coefficient Stochastic Frontier Application to Technical Efficiency Measurement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rebecca%20Owusu%20Coffie">Rebecca Owusu Coffie</a>, <a href="https://publications.waset.org/abstracts/search?q=Atakelty%20Hailu"> Atakelty Hailu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Variants of production frontier models have emerged, however, only a limited number of them are applied in empirical research. Hence the effects of these alternative frontier models are not well understood, particularly within sub-Saharan Africa. In this paper, we apply recent advances in the production frontier to examine levels of technical efficiency and efficiency drivers. Specifically, we compare the heteroscedastic parametric and the semiparametric stochastic smooth coefficient (SPSC) models. Using rice production data from Ghana, our empirical estimates reveal that alternative specification of efficiency estimators results in either downward or upward bias in the technical efficiency estimates. Methodologically, we find that the SPSC model is more suitable and generates high-efficiency estimates. Within the parametric framework, we find that parameterization of both the mean and variance of the pre-truncated function is the best model. For the drivers of technical efficiency, we observed that longer farm distances increase inefficiency through a reduction in labor productivity. High soil quality, however, increases productivity through increased land productivity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pre-truncated" title="pre-truncated">pre-truncated</a>, <a href="https://publications.waset.org/abstracts/search?q=rice%20production" title=" rice production"> rice production</a>, <a href="https://publications.waset.org/abstracts/search?q=smooth%20coefficient" title=" smooth coefficient"> smooth coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=technical%20efficiency" title=" technical efficiency"> technical efficiency</a> </p> <a href="https://publications.waset.org/abstracts/59500/heteroscedastic-parametric-and-semiparametric-smooth-coefficient-stochastic-frontier-application-to-technical-efficiency-measurement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59500.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">446</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8919</span> The Use of Stochastic Gradient Boosting Method for Multi-Model Combination of Rainfall-Runoff Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Phanida%20Phukoetphim">Phanida Phukoetphim</a>, <a href="https://publications.waset.org/abstracts/search?q=Asaad%20Y.%20Shamseldin"> Asaad Y. Shamseldin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-model%20combination" title="multi-model combination">multi-model combination</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall-runoff%20modeling" title=" rainfall-runoff modeling"> rainfall-runoff modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20gradient%20boosting" title=" stochastic gradient boosting"> stochastic gradient boosting</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a> </p> <a href="https://publications.waset.org/abstracts/3455/the-use-of-stochastic-gradient-boosting-method-for-multi-model-combination-of-rainfall-runoff-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3455.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">339</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8918</span> Forecasting Amman Stock Market Data Using a Hybrid Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Awajan">Ahmad Awajan</a>, <a href="https://publications.waset.org/abstracts/search?q=Sadam%20Al%20Wadi"> Sadam Al Wadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Holt-Winter%20method" title="Holt-Winter method">Holt-Winter method</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20mode%20decomposition" title=" empirical mode decomposition"> empirical mode decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=forecasting" title=" forecasting"> forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a> </p> <a href="https://publications.waset.org/abstracts/122857/forecasting-amman-stock-market-data-using-a-hybrid-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122857.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">129</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8917</span> Prediction of Formation Pressure Using Artificial Intelligence Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulmalek%20Ahmed">Abdulmalek Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Artificial%20Intelligence%20%28AI%29" title="Artificial Intelligence (AI)">Artificial Intelligence (AI)</a>, <a href="https://publications.waset.org/abstracts/search?q=Formation%20pressure" title=" Formation pressure"> Formation pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=Artificial%20Neural%20Networks%20%28ANN%29" title=" Artificial Neural Networks (ANN)"> Artificial Neural Networks (ANN)</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20Logic%20%28FL%29" title=" Fuzzy Logic (FL)"> Fuzzy Logic (FL)</a>, <a href="https://publications.waset.org/abstracts/search?q=Support%20Vector%20Machine%20%28SVM%29" title=" Support Vector Machine (SVM)"> Support Vector Machine (SVM)</a>, <a href="https://publications.waset.org/abstracts/search?q=Functional%20Networks%20%28FN%29" title=" Functional Networks (FN)"> Functional Networks (FN)</a>, <a href="https://publications.waset.org/abstracts/search?q=Radial%20Basis%20Function%20%28RBF%29" title=" Radial Basis Function (RBF)"> Radial Basis Function (RBF)</a> </p> <a href="https://publications.waset.org/abstracts/95931/prediction-of-formation-pressure-using-artificial-intelligence-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95931.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">149</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8916</span> Social Innovation Rediscovered: An Analysis of Empirical Research</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imen%20Douzi">Imen Douzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Ben%20Kahla"> Karim Ben Kahla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In spite of the growing attention for social innovation, it is still considered to be in a stage of infancy with minimal progress in theory development. Upon examining the field of study, one would have to conclude that, over the past two decades, academic research has focused primarily on establishing a conceptual foundation. This has resulted in a considerable stream of conceptual papers which have outnumbered empirical articles. Nevertheless, despite its growing popularity, scholars and practitioners are far from reaching a consensus as to what social innovation actually means which resulted in competing definitions and approaches within the field of social innovation and lack of unifying conceptual framework. This paper reviews empirical research studies on social innovation, classifies them along three dimensions and summarizes research findings for each of these dimensions. Preliminary to the analysis of empirical researches, an overview of different perspectives of social innovation is presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analysis%20of%20empirical%20research" title="analysis of empirical research">analysis of empirical research</a>, <a href="https://publications.waset.org/abstracts/search?q=definition" title=" definition"> definition</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20research" title=" empirical research"> empirical research</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20innovation%20perspectives" title=" social innovation perspectives"> social innovation perspectives</a> </p> <a href="https://publications.waset.org/abstracts/38783/social-innovation-rediscovered-an-analysis-of-empirical-research" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38783.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8915</span> Statistical Assessment of Models for Determination of Soil–Water Characteristic Curves of Sand Soils</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20J.%20Matlan">S. J. Matlan</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Mukhlisin"> M. Mukhlisin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Taha"> M. R. Taha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=soil-water%20characteristic%20curve%20%28SWCC%29" title="soil-water characteristic curve (SWCC)">soil-water characteristic curve (SWCC)</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20analysis" title=" statistical analysis"> statistical analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=unsaturated%20soil" title=" unsaturated soil"> unsaturated soil</a>, <a href="https://publications.waset.org/abstracts/search?q=geotechnical%20engineering" title=" geotechnical engineering"> geotechnical engineering</a> </p> <a href="https://publications.waset.org/abstracts/16494/statistical-assessment-of-models-for-determination-of-soil-water-characteristic-curves-of-sand-soils" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8914</span> Volatility Switching between Two Regimes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Josip%20Viskovi%C4%87">Josip Visković</a>, <a href="https://publications.waset.org/abstracts/search?q=Josip%20Arneri%C4%87"> Josip Arnerić</a>, <a href="https://publications.waset.org/abstracts/search?q=Ante%20Rozga"> Ante Rozga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modelling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=central%20and%20east%20European%20countries" title="central and east European countries">central and east European countries</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20crisis" title=" financial crisis"> financial crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20switching%20GARCH%20model" title=" Markov switching GARCH model"> Markov switching GARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=transition%20probabilities" title=" transition probabilities"> transition probabilities</a> </p> <a href="https://publications.waset.org/abstracts/2227/volatility-switching-between-two-regimes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2227.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">226</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=298">298</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=299">299</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=empirical%20models&amp;page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">&copy; 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">&times;</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>

Pages: 1 2 3 4 5 6 7 8 9 10