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Value Theory</title> <meta name="description" content="Search results for: Extreme Value Theory"> <meta name="keywords" content="Extreme Value Theory"> <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 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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="Extreme Value Theory"> <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> 5494</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Extreme Value Theory</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5494</span> Extreme Value Theory Applied in Reliability Analysis: Case Study of Diesel Generator Fans</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jelena%20Vucicevic">Jelena Vucicevic</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. In this paper, the results for the reliability of diesel generator fans were calculated through Extreme Value Theory. The Extreme Value Theory is not widely used in the engineering field. Its usage is well known in other areas such as hydrology, meteorology, finance. The significance of this theory is in the fact that unlike the other statistical methods it is focused on rare and extreme values, and not on average. It should be noted that this theory is not designed exclusively for extreme events, but for extreme values in any event. Therefore, this is a great opportunity to apply the theory and test if it could be applied in this situation. The significance of the work is the calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know the time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. The results achieved in this method will show the approximation of time for which the fans will work as they should, and the percentage of probability of fans working more than certain estimated time. Extreme Value Theory can be applied not only for rare and extreme events, but for any event that has values which we can consider as extreme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title="extreme value theory">extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=lifetime" title=" lifetime"> lifetime</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20analysis" title=" reliability analysis"> reliability analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=statistic" title=" statistic"> statistic</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20to%20failure" title=" time to failure"> time to failure</a> </p> <a href="https://publications.waset.org/abstracts/78201/extreme-value-theory-applied-in-reliability-analysis-case-study-of-diesel-generator-fans" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78201.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">327</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">5493</span> An Extension of the Generalized Extreme Value Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serge%20Provost">Serge Provost</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdous%20Saboor"> Abdous Saboor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A q-analogue of the generalized extreme value distribution which includes the Gumbel distribution is introduced. The additional parameter q allows for increased modeling flexibility. The resulting distribution can have a finite, semi-infinite or infinite support. It can also produce several types of hazard rate functions. The model parameters are determined by making use of the method of maximum likelihood. It will be shown that it compares favourably to three related distributions in connection with the modeling of a certain hydrological data set. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title="extreme value theory">extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20extreme%20value%20distribution" title=" generalized extreme value distribution"> generalized extreme value distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=goodness-of-fit%20statistics" title=" goodness-of-fit statistics"> goodness-of-fit statistics</a>, <a href="https://publications.waset.org/abstracts/search?q=Gumbel%20distribution" title=" Gumbel distribution"> Gumbel distribution</a> </p> <a href="https://publications.waset.org/abstracts/72656/an-extension-of-the-generalized-extreme-value-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72656.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">349</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">5492</span> A Bayesian Model with Improved Prior in Extreme Value Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eva%20L.%20Sanju%C3%A1n">Eva L. Sanjuán</a>, <a href="https://publications.waset.org/abstracts/search?q=Jacinto%20Mart%C3%ADn"> Jacinto Martín</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Isabel%20Parra"> M. Isabel Parra</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20M.%20Pizarro"> Mario M. Pizarro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Extreme Value Theory, inference estimation for the parameters of the distribution is made employing a small part of the observation values. When block maxima values are taken, many data are discarded. We developed a new Bayesian inference model to seize all the information provided by the data, introducing informative priors and using the relations between baseline and limit parameters. Firstly, we studied the accuracy of the new model for three baseline distributions that lead to a Gumbel extreme distribution: Exponential, Normal and Gumbel. Secondly, we considered mixtures of Normal variables, to simulate practical situations when data do not adjust to pure distributions, because of perturbations (noise). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bayesian%20inference" title="bayesian inference">bayesian inference</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=Gumbel%20distribution" title=" Gumbel distribution"> Gumbel distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=highly%20informative%20prior" title=" highly informative prior"> highly informative prior</a> </p> <a href="https://publications.waset.org/abstracts/141776/a-bayesian-model-with-improved-prior-in-extreme-value-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141776.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">198</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">5491</span> Modelling Operational Risk Using Extreme Value Theory and Skew t-Copulas via Bayesian Inference </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Betty%20Johanna%20Garzon%20Rozo">Betty Johanna Garzon Rozo</a>, <a href="https://publications.waset.org/abstracts/search?q=Jonathan%20Crook"> Jonathan Crook</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Moreira"> Fernando Moreira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. We propose a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severity distributions, and to calculate the capital for Operational Risk. This methodology simultaneously uses (i) several parametric distributions and an alternative mix distribution (the Lognormal for the body of losses and the Generalized Pareto Distribution for the tail) via extreme value theory using SAS®, (ii) the multivariate skew t-copula applied for the first time for operational losses and (iii) Bayesian theory to estimate new n-dimensional skew t-copula models via Markov chain Monte Carlo (MCMC) simulation. This paper analyses a newly operational loss data set, SAS Global Operational Risk Data [SAS OpRisk], to model operational risk at international financial institutions. All the severity models are constructed in SAS® 9.2. We implement the procedure PROC SEVERITY and PROC NLMIXED. This paper focuses in describing this implementation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=operational%20risk" title="operational risk">operational risk</a>, <a href="https://publications.waset.org/abstracts/search?q=loss%20distribution%20approach" title=" loss distribution approach"> loss distribution approach</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=copulas" title=" copulas"> copulas</a> </p> <a href="https://publications.waset.org/abstracts/19385/modelling-operational-risk-using-extreme-value-theory-and-skew-t-copulas-via-bayesian-inference" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19385.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">603</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">5490</span> Modeling of Maximum Rainfall Using Poisson-Generalized Pareto Distribution in Kigali, Rwanda</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Iyamuremye">Emmanuel Iyamuremye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=exceedances" title="exceedances">exceedances</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20Pareto%20distribution" title=" generalized Pareto distribution"> generalized Pareto distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=Poisson%20generalized%20Pareto%20distribution" title=" Poisson generalized Pareto distribution"> Poisson generalized Pareto distribution</a> </p> <a href="https://publications.waset.org/abstracts/127379/modeling-of-maximum-rainfall-using-poisson-generalized-pareto-distribution-in-kigali-rwanda" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127379.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">135</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">5489</span> An Application of Extreme Value Theory as a Risk Measurement Approach in Frontier Markets </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dany%20Ng%20Cheong%20Vee">Dany Ng Cheong Vee</a>, <a href="https://publications.waset.org/abstracts/search?q=Preethee%20Nunkoo%20Gonpot"> Preethee Nunkoo Gonpot</a>, <a href="https://publications.waset.org/abstracts/search?q=Noor%20Sookia"> Noor Sookia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that 'fat-tailedness' alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title="extreme value theory">extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20crisis%202008" title=" financial crisis 2008"> financial crisis 2008</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20at%20risk" title=" value at risk"> value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=frontier%20markets" title=" frontier markets"> frontier markets</a> </p> <a href="https://publications.waset.org/abstracts/6094/an-application-of-extreme-value-theory-as-a-risk-measurement-approach-in-frontier-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6094.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">276</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">5488</span> Extreme Value Modelling of Ghana Stock Exchange Indices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kwabena%20Asare">Kwabena Asare</a>, <a href="https://publications.waset.org/abstracts/search?q=Ezekiel%20N.%20N.%20Nortey"> Ezekiel N. N. Nortey</a>, <a href="https://publications.waset.org/abstracts/search?q=Felix%20O.%20Mettle"> Felix O. Mettle</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana Stock Exchange All-Shares indices (2000-2010) by applying the Extreme Value Theory to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before EVT method was applied. The Peak Over Threshold (POT) approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the Value at Risk (VaR) and Expected Shortfall (ES) risk measures at some high quantiles, based on the fitted GPD model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title="extreme value theory">extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=expected%20shortfall" title=" expected shortfall"> expected shortfall</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20pareto%20distribution" title=" generalized pareto distribution"> generalized pareto distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=peak%20over%20threshold" title=" peak over threshold"> peak over threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20at%20risk" title=" value at risk"> value at risk</a> </p> <a href="https://publications.waset.org/abstracts/35743/extreme-value-modelling-of-ghana-stock-exchange-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35743.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">557</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">5487</span> New Hybrid Method to Model Extreme Rainfalls</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Youness%20Laaroussi">Youness Laaroussi</a>, <a href="https://publications.waset.org/abstracts/search?q=Zine%20Elabidine%20Guennoun"> Zine Elabidine Guennoun</a>, <a href="https://publications.waset.org/abstracts/search?q=Amine%20Amar"> Amine Amar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modeling and forecasting dynamics of rainfall occurrences constitute one of the major topics, which have been largely treated by statisticians, hydrologists, climatologists and many other groups of scientists. In the same issue, we propose in the present paper a new hybrid method, which combines Extreme Values and fractal theories. We illustrate the use of our methodology for transformed Emberger Index series, constructed basing on data recorded in Oujda (Morocco). The index is treated at first by Peaks Over Threshold (POT) approach, to identify excess observations over an optimal threshold u. In the second step, we consider the resulting excess as a fractal object included in one dimensional space of time. We identify fractal dimension by the box counting. We discuss the prospect descriptions of rainfall data sets under Generalized Pareto Distribution, assured by Extreme Values Theory (EVT). We show that, despite of the appropriateness of return periods given by POT approach, the introduction of fractal dimension provides accurate interpretation results, which can ameliorate apprehension of rainfall occurrences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20values%20theory" title="extreme values theory">extreme values theory</a>, <a href="https://publications.waset.org/abstracts/search?q=fractals%20dimensions" title=" fractals dimensions"> fractals dimensions</a>, <a href="https://publications.waset.org/abstracts/search?q=peaks%20Over%20threshold" title=" peaks Over threshold"> peaks Over threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall%20occurrences" title=" rainfall occurrences"> rainfall occurrences</a> </p> <a href="https://publications.waset.org/abstracts/24836/new-hybrid-method-to-model-extreme-rainfalls" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24836.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">5486</span> 3D Printing Perceptual Models of Preference Using a Fuzzy Extreme Learning Machine Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xinyi%20Le">Xinyi Le</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3d%20printing" title="3d printing">3d printing</a>, <a href="https://publications.waset.org/abstracts/search?q=perceptual%20model" title=" perceptual model"> perceptual model</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20evaluation" title=" fuzzy evaluation"> fuzzy evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=data-driven%20approach" title=" data-driven approach"> data-driven approach</a> </p> <a href="https://publications.waset.org/abstracts/67233/3d-printing-perceptual-models-of-preference-using-a-fuzzy-extreme-learning-machine-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67233.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">438</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">5485</span> A Comparative Study of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Extreme Value Theory (EVT) Model in Modeling Value-at-Risk (VaR)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Longqing%20Li">Longqing Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Value-at-Risk" title="Value-at-Risk">Value-at-Risk</a>, <a href="https://publications.waset.org/abstracts/search?q=Extreme%20Value%20Theory" title=" Extreme Value Theory"> Extreme Value Theory</a>, <a href="https://publications.waset.org/abstracts/search?q=conditional%20EVT" title=" conditional EVT"> conditional EVT</a>, <a href="https://publications.waset.org/abstracts/search?q=backtesting" title=" backtesting"> backtesting</a> </p> <a href="https://publications.waset.org/abstracts/49589/a-comparative-study-of-generalized-autoregressive-conditional-heteroskedasticity-garch-and-extreme-value-theory-evt-model-in-modeling-value-at-risk-var" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49589.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">321</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">5484</span> Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Retius%20Chifurira">Retius Chifurira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20extreme%20value%20distribution" title="generalized extreme value distribution">generalized extreme value distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=general%20linear%20model" title=" general linear model"> general linear model</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20annual%20rainfall" title=" mean annual rainfall"> mean annual rainfall</a>, <a href="https://publications.waset.org/abstracts/search?q=meteorological%20drought%20probabilities" title=" meteorological drought probabilities"> meteorological drought probabilities</a> </p> <a href="https://publications.waset.org/abstracts/99321/generalized-extreme-value-regression-with-binary-dependent-variable-an-application-for-predicting-meteorological-drought-probabilities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99321.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">200</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">5483</span> The Impact of Distributed Epistemologies on Software Engineering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Smith">Thomas Smith</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many hackers worldwide would agree that, had it not been for linear-time theory, the refinement of Byzantine fault tolerance might never have occurred. After years of significant research into extreme programming, we validate the refinement of simulated annealing. Maw, our new framework for unstable theory, is the solution to all of these issues. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed" title="distributed">distributed</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20engineering" title=" software engineering"> software engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=DNS" title=" DNS"> DNS</a>, <a href="https://publications.waset.org/abstracts/search?q=DHCP" title=" DHCP"> DHCP</a> </p> <a href="https://publications.waset.org/abstracts/28477/the-impact-of-distributed-epistemologies-on-software-engineering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28477.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">355</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">5482</span> Contagion of the Global Financial Crisis and Its Impact on Systemic Risk in the Banking System: Extreme Value Theory Analysis in Six Emerging Asia Economies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ratna%20Kuswardani">Ratna Kuswardani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to study the impact of recent Global Financial Crisis (GFC) on 6 selected emerging Asian economies (Indonesia, Malaysia, Thailand, Philippines, Singapore, and South Korea). We first figure out the contagion of GFC from the US and Europe to the selected emerging Asian countries by studying the tail dependence of market stock returns between those countries. We apply the concept of Extreme Value Theory (EVT) to model the dependence between multiple returns series of variables under examination. We explore the factors causing the contagion between the regions. We find dependencies between markets that are influenced by their size, especially for large markets in emerging Asian countries that tend to have a higher dependency to the market in the more advanced country such as the U.S. and some countries in Europe. The results also suggest that the dependencies between market returns and bank stock returns in the same region tend to be higher than dependencies between these returns across two different regions. We extend our analysis by studying the impact of GFC on the systemic in the banking system. We also find that larger institution has more dependencies with the market stock, suggesting that larger size bank can cause disruption in the market. Further, the higher probability of extreme loss can be seen during the crisis period, which is shown by the non-linear dependency between the pre-crisis and the post-crisis period. Finally, our analysis suggests that systemic risk appears in the domestic banking systems in emerging Asia, as shown by the extreme dependencies within banks in the system. Overall, our results provide caution to policy makers and investors alike on the possible contagion of the impact of global financial crisis across different markets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=contagion" title="contagion">contagion</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20financial%20crisis" title=" global financial crisis"> global financial crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=systemic%20risk" title=" systemic risk"> systemic risk</a> </p> <a href="https://publications.waset.org/abstracts/99265/contagion-of-the-global-financial-crisis-and-its-impact-on-systemic-risk-in-the-banking-system-extreme-value-theory-analysis-in-six-emerging-asia-economies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99265.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">151</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">5481</span> Influence of Precipitation and Land Use on Extreme Flow in Prek Thnot River Basin of Mekong River in Cambodia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chhordaneath%20Hen">Chhordaneath Hen</a>, <a href="https://publications.waset.org/abstracts/search?q=Ty%20Sok"> Ty Sok</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilan%20Ich"> Ilan Ich</a>, <a href="https://publications.waset.org/abstracts/search?q=Ratboren%20Chan"> Ratboren Chan</a>, <a href="https://publications.waset.org/abstracts/search?q=Chantha%20Oeurng"> Chantha Oeurng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The damages caused by hydrological extremes such as flooding have been severe globally, and several research studies indicated extreme precipitations play a crucial role. Cambodia is one of the most vulnerable countries exposed to floods and drought as consequences of climate impact. Prek Thnot River Basin in the southwest part of Cambodia, which is in the plate and plateau region and a part of the Mekong Delta, was selected to investigate the changes in extreme precipitation and hydrological extreme. Furthermore, to develop a statistical relationship between these phenomena in this basin from 1995 to 2020 using Multiple Linear Regression. The precipitation and hydrological extreme were assessed via the attributes and trends of rainfall patterns during the study periods. The extreme flow was defined as a dependent variable, while the independent variables are various extreme precipitation indices. The study showed that all extreme precipitations indices (R10, R20, R35, CWD, R95p, R99p, and PRCPTOT) had increasing decency. However, the number of rain days per year had a decreasing tendency, which can conclude that extreme rainfall was more intense in a shorter period of the year. The study showed a similar relationship between extreme precipitation and hydrological extreme and land use change association with hydrological extreme. The direct combination of land use and precipitation equals 37% of the flood causes in this river. This study provided information on these two causes of flood events and an understanding of expectations of climate change consequences for flood and water resources management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20precipitation" title="extreme precipitation">extreme precipitation</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrological%20extreme" title=" hydrological extreme"> hydrological extreme</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20use" title=" land use"> land use</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20cover" title=" land cover"> land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=Prek%20Thnot%20river%20basin" title=" Prek Thnot river basin"> Prek Thnot river basin</a> </p> <a href="https://publications.waset.org/abstracts/155816/influence-of-precipitation-and-land-use-on-extreme-flow-in-prek-thnot-river-basin-of-mekong-river-in-cambodia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155816.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">111</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">5480</span> Possibility Theory Based Multi-Attribute Decision-Making: Application in Facility Location-Selection Problem under Uncertain and Extreme Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bezhan%20Ghvaberidze">Bezhan Ghvaberidze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A fuzzy multi-objective facility location-selection problem (FLSP) under uncertain and extreme environments based on possibility theory is developed. The model’s uncertain parameters in the q-rung orthopair fuzzy values are presented and transformed in the Dempster-Shaper’s belief structure environment. An objective function – distribution centers’ selection ranking index as an extension of Dempster’s extremal expectations under discrimination q-rung orthopair fuzzy information is constructed. Experts evaluate each humanitarian aid from distribution centers (HADC) against each of the uncertain factors. HADCs location problem is reduced to the bicriteria problem of partitioning the set of customers by the set of centers: (1) – Minimization of transportation costs; (2) – Maximization of centers’ selection ranking indexes. Partitioning type constraints are also constructed. For an illustration of the obtained results, a numerical example is created from the facility location-selection problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FLSP" title="FLSP">FLSP</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20combinatorial%20optimization%20problem" title=" multi-objective combinatorial optimization problem"> multi-objective combinatorial optimization problem</a>, <a href="https://publications.waset.org/abstracts/search?q=evidence%20theory" title=" evidence theory"> evidence theory</a>, <a href="https://publications.waset.org/abstracts/search?q=HADC" title=" HADC"> HADC</a>, <a href="https://publications.waset.org/abstracts/search?q=q-rung%20orthopair%20fuzzy%20set" title=" q-rung orthopair fuzzy set"> q-rung orthopair fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=possibility%20theory" title=" possibility theory"> possibility theory</a> </p> <a href="https://publications.waset.org/abstracts/161061/possibility-theory-based-multi-attribute-decision-making-application-in-facility-location-selection-problem-under-uncertain-and-extreme-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161061.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">119</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">5479</span> Estimating The Population Mean by Using Stratified Double Extreme Ranked Set Sample</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20I.%20Syam">Mahmoud I. Syam</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamarulzaman%20Ibrahim"> Kamarulzaman Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Amer%20I.%20Al-Omari"> Amer I. Al-Omari </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stratified double extreme ranked set sampling (SDERSS) method is introduced and considered for estimating the population mean. The SDERSS is compared with the simple random sampling (SRS), stratified ranked set sampling (SRSS) and stratified simple set sampling (SSRS). It is shown that the SDERSS estimator is an unbiased of the population mean and more efficient than the estimators using SRS, SRSS and SSRS when the underlying distribution of the variable of interest is symmetric or asymmetric. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=double%20extreme%20ranked%20set%20sampling" title="double extreme ranked set sampling">double extreme ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20ranked%20set%20sampling" title=" extreme ranked set sampling"> extreme ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=ranked%20set%20sampling" title=" ranked set sampling"> ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=stratified%20double%20extreme%20ranked%20set%20sampling" title=" stratified double extreme ranked set sampling"> stratified double extreme ranked set sampling</a> </p> <a href="https://publications.waset.org/abstracts/25207/estimating-the-population-mean-by-using-stratified-double-extreme-ranked-set-sample" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25207.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">456</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">5478</span> Statistical Modelling of Maximum Temperature in Rwanda Using Extreme Value Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Iyamuremye">Emmanuel Iyamuremye</a>, <a href="https://publications.waset.org/abstracts/search?q=Edouard%20Singirankabo"> Edouard Singirankabo</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexis%20Habineza"> Alexis Habineza</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunvirusaba%20Nelson"> Yunvirusaba Nelson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20warming" title=" global warming"> global warming</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title=" extreme value theory"> extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=rwanda" title=" rwanda"> rwanda</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature" title=" temperature"> temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=generalised%20extreme%20value%20distribution" title=" generalised extreme value distribution"> generalised extreme value distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=generalised%20pareto%20distribution" title=" generalised pareto distribution"> generalised pareto distribution</a> </p> <a href="https://publications.waset.org/abstracts/132786/statistical-modelling-of-maximum-temperature-in-rwanda-using-extreme-value-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132786.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">183</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">5477</span> Orthogonal Basis Extreme Learning Algorithm and Function Approximation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ying%20Li">Ying Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Li"> Yan Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title="neural network">neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20basis%20extreme%20learning" title=" orthogonal basis extreme learning"> orthogonal basis extreme learning</a>, <a href="https://publications.waset.org/abstracts/search?q=function%20approximation" title=" function approximation"> function approximation</a> </p> <a href="https://publications.waset.org/abstracts/15129/orthogonal-basis-extreme-learning-algorithm-and-function-approximation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15129.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">534</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">5476</span> Climate Change and Extreme Weather: Understanding Interconnections and Implications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Johnstone%20Walubengo%20Wangusi">Johnstone Walubengo Wangusi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Climate change is undeniably altering the frequency, intensity, and geographic distribution of extreme weather events worldwide. In this paper, we explore the complex interconnections between climate change and extreme weather phenomena, drawing upon research from atmospheric science, geology, and climatology. We examine the underlying mechanisms driving these changes, the impacts on natural ecosystems and human societies, and strategies for adaptation and mitigation. By synthesizing insights from interdisciplinary research, this paper aims to provide a comprehensive understanding of the multifaceted relationship between climate change and extreme weather, informing efforts to address the challenges posed by a changing climate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20weather" title=" extreme weather"> extreme weather</a>, <a href="https://publications.waset.org/abstracts/search?q=atmospheric%20science" title=" atmospheric science"> atmospheric science</a>, <a href="https://publications.waset.org/abstracts/search?q=geology" title=" geology"> geology</a>, <a href="https://publications.waset.org/abstracts/search?q=climatology" title=" climatology"> climatology</a>, <a href="https://publications.waset.org/abstracts/search?q=impacts" title=" impacts"> impacts</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptation" title=" adaptation"> adaptation</a>, <a href="https://publications.waset.org/abstracts/search?q=mitigation" title=" mitigation"> mitigation</a> </p> <a href="https://publications.waset.org/abstracts/184530/climate-change-and-extreme-weather-understanding-interconnections-and-implications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184530.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">64</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">5475</span> Application of Stochastic Models to Annual Extreme Streamflow Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karim%20Hamidi%20Machekposhti">Karim Hamidi Machekposhti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Sedghi"> Hossein Sedghi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stochastic%20models" title="stochastic models">stochastic models</a>, <a href="https://publications.waset.org/abstracts/search?q=ARIMA" title=" ARIMA"> ARIMA</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20streamflow" title=" extreme streamflow"> extreme streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=Karkheh%20river" title=" Karkheh river"> Karkheh river</a> </p> <a href="https://publications.waset.org/abstracts/97759/application-of-stochastic-models-to-annual-extreme-streamflow-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97759.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">148</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">5474</span> Prediction of Extreme Precipitation in East Asia Using Complex Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feng%20Guolin">Feng Guolin</a>, <a href="https://publications.waset.org/abstracts/search?q=Gong%20Zhiqiang"> Gong Zhiqiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=synchronization" title="synchronization">synchronization</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20network" title=" climate network"> climate network</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall" title=" rainfall"> rainfall</a> </p> <a href="https://publications.waset.org/abstracts/64827/prediction-of-extreme-precipitation-in-east-asia-using-complex-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64827.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">442</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">5473</span> Analysis of the Statistical Characterization of Significant Wave Data Exceedances for Designing Offshore Structures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rui%20Teixeira">Rui Teixeira</a>, <a href="https://publications.waset.org/abstracts/search?q=Alan%20O%E2%80%99Connor"> Alan O’Connor</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Nogal"> Maria Nogal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20events" title="extreme events">extreme events</a>, <a href="https://publications.waset.org/abstracts/search?q=offshore%20structures" title=" offshore structures"> offshore structures</a>, <a href="https://publications.waset.org/abstracts/search?q=peak-over-threshold" title=" peak-over-threshold"> peak-over-threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=significant%20wave%20data" title=" significant wave data"> significant wave data</a> </p> <a href="https://publications.waset.org/abstracts/56287/analysis-of-the-statistical-characterization-of-significant-wave-data-exceedances-for-designing-offshore-structures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56287.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">272</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">5472</span> Applying the Extreme-Based Teaching Model in Post-Secondary Online Classroom Setting: A Field Experiment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leon%20Pan">Leon Pan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme-based%20teaching%20model" title="extreme-based teaching model">extreme-based teaching model</a>, <a href="https://publications.waset.org/abstracts/search?q=innovative%20pedagogical%20methods" title=" innovative pedagogical methods"> innovative pedagogical methods</a>, <a href="https://publications.waset.org/abstracts/search?q=project-based%20learning" title=" project-based learning"> project-based learning</a>, <a href="https://publications.waset.org/abstracts/search?q=team-based%20learning" title=" team-based learning"> team-based learning</a> </p> <a href="https://publications.waset.org/abstracts/171936/applying-the-extreme-based-teaching-model-in-post-secondary-online-classroom-setting-a-field-experiment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171936.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">59</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">5471</span> Gradient-Based Reliability Optimization of Integrated Energy Systems Under Extreme Weather Conditions: A Case Study in Ningbo, China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Da%20LI">Da LI</a>, <a href="https://publications.waset.org/abstracts/search?q=Peng%20Xu"> Peng Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent extreme weather events, such as the 2021 European floods and North American heatwaves, have exposed the vulnerability of energy systems to both extreme demand scenarios and potential physical damage. Current integrated energy system designs often overlook performance under these challenging conditions. This research, focusing on a regional integrated energy system in Ningbo, China, proposes a distinct design method to optimize system reliability during extreme events. A multi-scenario model was developed, encompassing various extreme load conditions and potential system damages caused by severe weather. Based on this model, a comprehensive reliability improvement scheme was designed, incorporating a gradient approach to address different levels of disaster severity through the integration of advanced technologies like distributed energy storage. The scheme's effectiveness was validated through Monte Carlo simulations. Results demonstrate significant enhancements in energy supply reliability and peak load reduction capability under extreme scenarios. The findings provide several insights for improving energy system adaptability in the face of climate-induced challenges, offering valuable references for building reliable energy infrastructure capable of withstanding both extreme demands and physical threats across a spectrum of disaster intensities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20weather%20events" title="extreme weather events">extreme weather events</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20energy%20systems" title=" integrated energy systems"> integrated energy systems</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20improvement" title=" reliability improvement"> reliability improvement</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change%20adaptation" title=" climate change adaptation"> climate change adaptation</a> </p> <a href="https://publications.waset.org/abstracts/190789/gradient-based-reliability-optimization-of-integrated-energy-systems-under-extreme-weather-conditions-a-case-study-in-ningbo-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190789.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">25</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">5470</span> Gravitational Frequency Shifts for Photons and Particles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jing-Gang%20Xie">Jing-Gang Xie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The research, in this case, considers the integration of the Quantum Field Theory and the General Relativity Theory. As two successful models in explaining behaviors of particles, they are incompatible since they work at different masses and scales of energy, with the evidence that regards the description of black holes and universe formation. It is so considering previous efforts in merging the two theories, including the likes of the String Theory, Quantum Gravity models, and others. In a bid to prove an actionable experiment, the paper’s approach starts with the derivations of the existing theories at present. It goes on to test the derivations by applying the same initial assumptions, coupled with several deviations. The resulting equations get similar results to those of classical Newton model, quantum mechanics, and general relativity as long as conditions are normal. However, outcomes are different when conditions are extreme, specifically with no breakdowns even for less than Schwarzschild radius, or at Planck length cases. Even so, it proves the possibilities of integrating the two theories. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=general%20relativity%20theory" title="general relativity theory">general relativity theory</a>, <a href="https://publications.waset.org/abstracts/search?q=particles" title=" particles"> particles</a>, <a href="https://publications.waset.org/abstracts/search?q=photons" title=" photons"> photons</a>, <a href="https://publications.waset.org/abstracts/search?q=Quantum%20Gravity%20Model" title=" Quantum Gravity Model"> Quantum Gravity Model</a>, <a href="https://publications.waset.org/abstracts/search?q=gravitational%20frequency%20shift" title=" gravitational frequency shift"> gravitational frequency shift</a> </p> <a href="https://publications.waset.org/abstracts/59744/gravitational-frequency-shifts-for-photons-and-particles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59744.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">359</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">5469</span> A Machine Learning-Based Approach to Capture Extreme Rainfall Events</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Willy%20Mbenza">Willy Mbenza</a>, <a href="https://publications.waset.org/abstracts/search?q=Sho%20Kenjiro"> Sho Kenjiro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20%28ML%29" title="machine learning (ML)">machine learning (ML)</a>, <a href="https://publications.waset.org/abstracts/search?q=predictions" title=" predictions"> predictions</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall%20events" title=" rainfall events"> rainfall events</a>, <a href="https://publications.waset.org/abstracts/search?q=regional%20variables" title=" regional variables"> regional variables</a> </p> <a href="https://publications.waset.org/abstracts/168878/a-machine-learning-based-approach-to-capture-extreme-rainfall-events" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168878.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">88</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">5468</span> Changes in Temperature and Precipitation Extremes in Northern Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chakrit%20Chotamonsak">Chakrit Chotamonsak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was analyzed changes in temperature and precipitation extremes in northern Thailand for the period 1981-2011.The study includes an analysis of the average and trends of changes in temperature and precipitation using 22 climate indices, related to the intensity, frequency and duration of extreme climate events. The results showed that the averaged trend of maximum, minimum and mean temperature is likely to increase over the study area in rate of 0.5, 0.9 and 0.7 °C in last 30 years. Changes in temperature at nighttime, then rising at a rate higher daytime is resulting to decline of diurnal temperature range throughout the area. Trend of changes in average precipitation during the year 1981-2011 is expected to increase at an average rate of 21%. The intensity of extreme temperature events is increasing almost all station. In particular, the changes of the night were unusually hot has intensified throughout the region. In some provinces such as Chiang Mai and Lampang are likely be faced with the severity of hot days and hot nights in increasing rate. Frequency of extreme temperature events are likely to increase each station, especially hot days, and hot nights are increasing at a rate of 2.38 and 3.58 days per decade. Changes in the cold days and cold nights are declining at a rate of 0.82 and 3.03 days per decade. The duration of extreme temperature events is expected to increase the events hot in every station. An average of 17.8 days per decade for the number of consecutive cold winter nights likely shortens the rate of 2.90 days per decade. The analysis of the precipitation indices reveals the intensity of extreme precipitation is increasing almost across the region. The intensify expressed the heavy rain in one day (Rx1day) and very heavy rain accumulated in 5 days (RX5day) which is likely to increase, and very heavy rainfall is likely to increase in intensity. Frequency of extreme precipitation events is likely to increase over the station. The average frequency of heavy precipitation events increased xxx days per decade. The duration of extreme precipitation events, such as the consecutive dry days are likely to reduce the numbers almost all station while the consecutive wet days tends to increase and decrease at different numbers in different areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20extreme" title="climate extreme">climate extreme</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature%20extreme" title=" temperature extreme"> temperature extreme</a>, <a href="https://publications.waset.org/abstracts/search?q=precipitation%20extreme" title=" precipitation extreme"> precipitation extreme</a>, <a href="https://publications.waset.org/abstracts/search?q=Northern%20Thailand" title=" Northern Thailand"> Northern Thailand</a> </p> <a href="https://publications.waset.org/abstracts/35651/changes-in-temperature-and-precipitation-extremes-in-northern-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35651.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">283</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">5467</span> Damage Cost for Private Property by Extreme Wind over the past 10 Years in Korea</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gou-Moon%20Choi">Gou-Moon Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Woo-Young%20Jung"> Woo-Young Jung</a>, <a href="https://publications.waset.org/abstracts/search?q=Chan-Young%20Yune"> Chan-Young Yune</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, the natural disaster has increased worldwide. In Korea, the damage to life and property caused by a typhoon, heavy rain, heavy snow, and an extreme wind also increases every year. Among natural disasters, the frequency and the strength of wind have increased because sea surface temperature has risen due to the increase of the average temperature of the Earth. In the case of extreme wind disaster, it is impossible to control or reduce the occurrence, and the recovery cost always exceeds the damage cost. Therefore, quantitative estimation of the damage cost for extreme wind needs to be established beforehand to install proactive countermeasures. In this study, the damage cost for private properties was analyzed based on the data for the past 10 years in Korea. The damage cost curve was also suggested for the metropolitan cities and provinces. The result shows the possibility for the regional application of the damage cost curve because the damage cost of the regional area is estimated based on the cost of cities and provinces. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=damage%20cost" title="damage cost">damage cost</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20wind" title=" extreme wind"> extreme wind</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20disaster" title=" natural disaster"> natural disaster</a>, <a href="https://publications.waset.org/abstracts/search?q=private%20property" title=" private property"> private property</a> </p> <a href="https://publications.waset.org/abstracts/44424/damage-cost-for-private-property-by-extreme-wind-over-the-past-10-years-in-korea" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44424.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">305</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">5466</span> The Theory of Relativity (K)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Igor%20Vladimirovich%20Kuzminov">Igor Vladimirovich Kuzminov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The proposed article is an alternative version of the Theory of Relativity. The version is based on the concepts of classical Newtonian physics and does not deny the existing calculation base. The proposed theory completely denies Einstein's existing Theory of Relativity. The only thing that connects these theories is that the proposed theory is also built on postulates. The proposed theory is intended to establish the foundation of classical Newtonian physics. The proposed theory is intended to establish continuity in the development of the fundamentals of physics and is intended to eliminate all kinds of speculation in explanations of physical phenomena. An example of such speculation is Einstein's Theory of Relativity (E). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=the%20theory%20of%20relativity" title="the theory of relativity">the theory of relativity</a>, <a href="https://publications.waset.org/abstracts/search?q=postulates%20of%20the%20theory%20of%20relativity" title=" postulates of the theory of relativity"> postulates of the theory of relativity</a>, <a href="https://publications.waset.org/abstracts/search?q=criticism%20of%20Einstein%27s%20theory" title=" criticism of Einstein's theory"> criticism of Einstein's theory</a>, <a href="https://publications.waset.org/abstracts/search?q=classical%20physics" title=" classical physics"> classical physics</a> </p> <a href="https://publications.waset.org/abstracts/188535/the-theory-of-relativity-k" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188535.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">50</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">5465</span> The Magic Bullet in Africa: Exploring an Alternative Theoretical Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Nkrumah">Daniel Nkrumah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Magic Bullet theory was a popular media effect theory that defined the power of the mass media in altering beliefs and perceptions of its audiences. However, following the People's Choice study, the theory was said to have been disproved and was supplanted by the Two-Step Flow Theory. This paper examines the relevance of the Magic Bullet theory in Africa and establishes whether it is still relevant in Africa's media spaces and societies. Using selected cases on the continent, it adopts a grounded theory approach and explores a new theoretical model that attempts to enforce an argument that the Two-Step Flow theory though important and valid, was ill-conceived as a direct replacement to the Magic Bullet theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=magic%20bullet%20theory" title="magic bullet theory">magic bullet theory</a>, <a href="https://publications.waset.org/abstracts/search?q=two-step%20flow%20theory" title=" two-step flow theory"> two-step flow theory</a>, <a href="https://publications.waset.org/abstracts/search?q=media%20effects" title=" media effects"> media effects</a>, <a href="https://publications.waset.org/abstracts/search?q=african%20media" title=" african media"> african media</a> </p> <a href="https://publications.waset.org/abstracts/168592/the-magic-bullet-in-africa-exploring-an-alternative-theoretical-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168592.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">127</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=Extreme%20Value%20Theory&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Extreme%20Value%20Theory&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Extreme%20Value%20Theory&page=4">4</a></li> <li class="page-item"><a class="page-link" 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