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regression</title> <meta name="description" content="Search results for: multiple regression"> <meta name="keywords" content="multiple regression"> <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 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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="multiple regression"> <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> 7213</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: multiple regression</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7213</span> Multi-Linear Regression Based Prediction of Mass Transfer by Multiple Plunging Jets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Deswal">S. Deswal</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Pal"> M. Pal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90O; whereas, multiple inclined plunging jets have jet impact angle of θ = 600. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (KLa) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modelling mass transfer by multiple plunging jets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mass%20transfer" title="mass transfer">mass transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20plunging%20jets" title=" multiple plunging jets"> multiple plunging jets</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-linear%20regression" title=" multi-linear regression"> multi-linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=earth%20sciences" title=" earth sciences"> earth sciences</a> </p> <a href="https://publications.waset.org/abstracts/5905/multi-linear-regression-based-prediction-of-mass-transfer-by-multiple-plunging-jets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5905.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">461</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">7212</span> Internet Purchases in European Union Countries: Multiple Linear Regression Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ksenija%20Dumi%C4%8Di%C4%87">Ksenija Dumičić</a>, <a href="https://publications.waset.org/abstracts/search?q=Anita%20%C4%8Ceh%20%C4%8Casni"> Anita Čeh Časni</a>, <a href="https://publications.waset.org/abstracts/search?q=Irena%20Pali%C4%87"> Irena Palić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analysed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analysed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=European%20union" title="European union">European union</a>, <a href="https://publications.waset.org/abstracts/search?q=Internet%20purchases" title=" Internet purchases"> Internet purchases</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression%20model" title=" multiple linear regression model"> multiple linear regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=outlier" title=" outlier"> outlier</a> </p> <a href="https://publications.waset.org/abstracts/2650/internet-purchases-in-european-union-countries-multiple-linear-regression-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2650.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">302</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">7211</span> Application and Verification of Regression Model to Landslide Susceptibility Mapping</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masood%20Beheshtirad">Masood Beheshtirad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=mapping" title=" mapping"> mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20model" title=" multiple model"> multiple model</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/25864/application-and-verification-of-regression-model-to-landslide-susceptibility-mapping" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25864.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">323</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">7210</span> Optimization of Machine Learning Regression Results: An Application on Health Expenditures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Songul%20Cinaroglu">Songul Cinaroglu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=lasso%20regression" title=" lasso regression"> lasso regression</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20regression" title=" random forest regression"> random forest regression</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20regression" title=" support vector regression"> support vector regression</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperparameter%20tuning" title=" hyperparameter tuning"> hyperparameter tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20expenditure" title=" health expenditure"> health expenditure</a> </p> <a href="https://publications.waset.org/abstracts/97629/optimization-of-machine-learning-regression-results-an-application-on-health-expenditures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97629.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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7209</span> The Strengths and Limitations of the Statistical Modeling of Complex Social Phenomenon: Focusing on SEM, Path Analysis, or Multiple Regression Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jihye%20Jeon">Jihye Jeon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression" title="multiple regression">multiple regression</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20analysis" title=" path analysis"> path analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20equation%20models" title=" structural equation models"> structural equation models</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20modeling" title=" statistical modeling"> statistical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20and%20psychological%20phenomenon" title=" social and psychological phenomenon"> social and psychological phenomenon</a> </p> <a href="https://publications.waset.org/abstracts/31464/the-strengths-and-limitations-of-the-statistical-modeling-of-complex-social-phenomenon-focusing-on-sem-path-analysis-or-multiple-regression-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31464.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">652</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">7208</span> Ketones Emission during Pad Printing Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kiurski%20S.%20Jelena">Kiurski S. Jelena</a>, <a href="https://publications.waset.org/abstracts/search?q=Aksentijevi%C4%87%20M.%20Sne%C5%BEana"> Aksentijević M. Snežana</a>, <a href="https://publications.waset.org/abstracts/search?q=Oros%20B.%20Ivana"> Oros B. Ivana</a>, <a href="https://publications.waset.org/abstracts/search?q=Keci%C4%87%20S.%20Vesna"> Kecić S. Vesna</a>, <a href="https://publications.waset.org/abstracts/search?q=Djogo%20Z.%20Maja"> Djogo Z. Maja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper investigates the effect of light intensity on the formation of two ketones, acetone and methyl ethyl ketone, in working premises of five pad printing departments in Novi Sad, Serbia. Multiple linear regression analysis examined the form of interdependency concentrations of methyl ethyl ketone, acetone and light intensity in five printing presses at seven sampling points, using Statistica software package version 10th. The results show an average stacking variation investigated variable and can be presented by the general regression model: y = b0 + b1xi1 + b2xi2. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acetone" title="acetone">acetone</a>, <a href="https://publications.waset.org/abstracts/search?q=methyl%20ethyl%20ketone" title=" methyl ethyl ketone"> methyl ethyl ketone</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression%20analysis" title=" multiple linear regression analysis"> multiple linear regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=pad%20printing" title=" pad printing"> pad printing</a> </p> <a href="https://publications.waset.org/abstracts/4798/ketones-emission-during-pad-printing-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4798.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">419</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">7207</span> Interference among Lambsquarters and Oil Rapeseed Cultivars </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reza%20Siyami">Reza Siyami</a>, <a href="https://publications.waset.org/abstracts/search?q=Bahram%20Mirshekari"> Bahram Mirshekari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seed and oil yield of rapeseed is considerably affected by weeds interference including mustard (Sinapis arvensis L.), lambsquarters (Chenopodium album L.) and redroot pigweed (Amaranthus retroflexus L.) throughout the East Azerbaijan province in Iran. To formulate the relationship between four independent growth variables measured in our experiment with a dependent variable, multiple regression analysis was carried out for the weed leaves number per plant (X1), green cover percentage (X2), LAI (X3) and leaf area per plant (X4) as independent variables and rapeseed oil yield as a dependent variable. The multiple regression equation is shown as follows: Seed essential oil yield (kg/ha) = 0.156 + 0.0325 (X1) + 0.0489 (X2) + 0.0415 (X3) + 0.133 (X4). Furthermore, the stepwise regression analysis was also carried out for the data obtained to test the significance of the independent variables affecting the oil yield as a dependent variable. The resulted stepwise regression equation is shown as follows: Oil yield = 4.42 + 0.0841 (X2) + 0.0801 (X3); R2 = 81.5. The stepwise regression analysis verified that the green cover percentage and LAI of weed had a marked increasing effect on the oil yield of rapeseed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=green%20cover%20percentage" title="green cover percentage">green cover percentage</a>, <a href="https://publications.waset.org/abstracts/search?q=independent%20variable" title=" independent variable"> independent variable</a>, <a href="https://publications.waset.org/abstracts/search?q=interference" title=" interference"> interference</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/35826/interference-among-lambsquarters-and-oil-rapeseed-cultivars" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35826.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">420</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">7206</span> Multiobjective Optimization of a Pharmaceutical Formulation Using Regression Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Satya%20Eswari">J. Satya Eswari</a>, <a href="https://publications.waset.org/abstracts/search?q=Ch.%20Venkateswarlu"> Ch. Venkateswarlu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pharmaceutical%20formulation" title="pharmaceutical formulation">pharmaceutical formulation</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression%20model" title=" multiple regression model"> multiple regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=response%20surface%20method" title=" response surface method"> response surface method</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20basis%20function%20network" title=" radial basis function network"> radial basis function network</a>, <a href="https://publications.waset.org/abstracts/search?q=differential%20evolution" title=" differential evolution"> differential evolution</a>, <a href="https://publications.waset.org/abstracts/search?q=multiobjective%20optimization" title=" multiobjective optimization"> multiobjective optimization</a> </p> <a href="https://publications.waset.org/abstracts/62859/multiobjective-optimization-of-a-pharmaceutical-formulation-using-regression-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62859.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">409</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">7205</span> Exploration and Evaluation of the Effect of Multiple Countermeasures on Road Safety</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Atheer%20Al-Nuaimi">Atheer Al-Nuaimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Harry%20Evdorides"> Harry Evdorides</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=international%20road%20assessment%20program" title="international road assessment program">international road assessment program</a>, <a href="https://publications.waset.org/abstracts/search?q=negative%20binomial" title=" negative binomial"> negative binomial</a>, <a href="https://publications.waset.org/abstracts/search?q=road%20multiple%20countermeasures" title=" road multiple countermeasures"> road multiple countermeasures</a>, <a href="https://publications.waset.org/abstracts/search?q=road%20safety" title=" road safety"> road safety</a> </p> <a href="https://publications.waset.org/abstracts/63990/exploration-and-evaluation-of-the-effect-of-multiple-countermeasures-on-road-safety" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63990.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">240</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">7204</span> Behind Fuzzy Regression Approach: An Exploration Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lavinia%20B.%20Dulla">Lavinia B. Dulla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression%20approach" title="fuzzy regression approach">fuzzy regression approach</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20fuzziness%20criterion" title=" minimum fuzziness criterion"> minimum fuzziness criterion</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20regression" title=" interval regression"> interval regression</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20interval" title=" prediction interval"> prediction interval</a> </p> <a href="https://publications.waset.org/abstracts/139364/behind-fuzzy-regression-approach-an-exploration-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139364.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">298</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">7203</span> The Factors of Supply Chain Collaboration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghada%20Soltane">Ghada Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this study was to identify factors impacting supply chain collaboration. a quantitative study was carried out on a sample of 84 Tunisian industrial companies. To verify the research hypotheses and test the direct effect of these factors on supply chain collaboration a multiple regression method was used using SPSS 26 software. The results show that there are four factors direct effects that affect supply chain collaboration in a meaningful and positive way, including: trust, engagement, information sharing and information quality <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=supply%20chain%20collaboration" title="supply chain collaboration">supply chain collaboration</a>, <a href="https://publications.waset.org/abstracts/search?q=factors%20of%20collaboration" title=" factors of collaboration"> factors of collaboration</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression" title=" multiple regression"> multiple regression</a> </p> <a href="https://publications.waset.org/abstracts/185892/the-factors-of-supply-chain-collaboration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185892.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">49</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">7202</span> SVM-Based Modeling of Mass Transfer Potential of Multiple Plunging Jets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Surinder%20Deswal">Surinder Deswal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahesh%20Pal"> Mahesh Pal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mass%20transfer" title="mass transfer">mass transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20plunging%20jets" title=" multiple plunging jets"> multiple plunging jets</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machines" title=" support vector machines"> support vector machines</a>, <a href="https://publications.waset.org/abstracts/search?q=ecological%20sciences" title=" ecological sciences"> ecological sciences</a> </p> <a href="https://publications.waset.org/abstracts/9906/svm-based-modeling-of-mass-transfer-potential-of-multiple-plunging-jets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9906.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">464</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">7201</span> Quantitative Structure Activity Relationship and Insilco Docking of Substituted 1,3,4-Oxadiazole Derivatives as Potential Glucosamine-6-Phosphate Synthase Inhibitors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suman%20Bala">Suman Bala</a>, <a href="https://publications.waset.org/abstracts/search?q=Sunil%20Kamboj"> Sunil Kamboj</a>, <a href="https://publications.waset.org/abstracts/search?q=Vipin%20Saini"> Vipin Saini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quantitative Structure Activity Relationship (QSAR) analysis has been developed to relate antifungal activity of novel substituted 1,3,4-oxadiazole against <em>Candida albicans</em> and <em>Aspergillus niger</em> using computer assisted multiple regression analysis. The study has shown the better relationship between antifungal activities with respect to various descriptors established by multiple regression analysis. The analysis has shown statistically significant correlation with R<sup>2</sup> values 0.932 and 0.782 against <em>Candida albicans</em> and <em>Aspergillus niger</em> respectively. These derivatives were further subjected to molecular docking studies to investigate the interactions between the target compounds and amino acid residues present in the active site of glucosamine-6-phosphate synthase. All the synthesized compounds have better docking score as compared to standard fluconazole. Our results could be used for the further design as well as development of optimal and potential antifungal agents. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=1" title="1">1</a>, <a href="https://publications.waset.org/abstracts/search?q=3" title="3">3</a>, <a href="https://publications.waset.org/abstracts/search?q=4-oxadiazole" title="4-oxadiazole">4-oxadiazole</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR" title=" QSAR"> QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=docking" title=" docking"> docking</a>, <a href="https://publications.waset.org/abstracts/search?q=glucosamine-6-phosphate%20synthase" title=" glucosamine-6-phosphate synthase"> glucosamine-6-phosphate synthase</a> </p> <a href="https://publications.waset.org/abstracts/37494/quantitative-structure-activity-relationship-and-insilco-docking-of-substituted-134-oxadiazole-derivatives-as-potential-glucosamine-6-phosphate-synthase-inhibitors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37494.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">341</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">7200</span> Effect of Drying on the Concrete Structures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Brahma">A. Brahma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The drying of hydraulics materials is unavoidable and conducted to important spontaneous deformations. In this study, we show that it is possible to describe the drying shrinkage of the high-performance concrete by a simple expression. A multiple regression model was developed for the prediction of the drying shrinkage of the high-performance concrete. The assessment of the proposed model has been done by a set of statistical tests. The model developed takes in consideration the main parameters of confection and conservation. There was a very good agreement between drying shrinkage predicted by the multiple regression model and experimental results. The developed model adjusts easily to all hydraulic concrete types. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydraulic%20concretes" title="hydraulic concretes">hydraulic concretes</a>, <a href="https://publications.waset.org/abstracts/search?q=drying" title=" drying"> drying</a>, <a href="https://publications.waset.org/abstracts/search?q=shrinkage" title=" shrinkage"> shrinkage</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=modeling" title=" modeling"> modeling</a> </p> <a href="https://publications.waset.org/abstracts/15705/effect-of-drying-on-the-concrete-structures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15705.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">368</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">7199</span> Competition between Regression Technique and Statistical Learning Models for Predicting Credit Risk Management</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 objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=credit%20risk%20management" title="credit risk management">credit risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20components%20analysis" title=" principal components analysis"> principal components analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machines" title=" support vector machines"> support vector machines</a> </p> <a href="https://publications.waset.org/abstracts/103512/competition-between-regression-technique-and-statistical-learning-models-for-predicting-credit-risk-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103512.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">150</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">7198</span> A Study of User Awareness and Attitudes Towards Civil-ID Authentication in Oman’s Electronic Services</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raya%20Al%20Khayari">Raya Al Khayari</a>, <a href="https://publications.waset.org/abstracts/search?q=Rasha%20Al%20Jassim"> Rasha Al Jassim</a>, <a href="https://publications.waset.org/abstracts/search?q=Muna%20Al%20Balushi"> Muna Al Balushi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatma%20Al%20Moqbali"> Fatma Al Moqbali</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20El%20Hajjar"> Said El Hajjar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=civil-id%20disclosure" title="civil-id disclosure">civil-id disclosure</a>, <a href="https://publications.waset.org/abstracts/search?q=awareness" title=" awareness"> awareness</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20regression" title=" linear regression"> linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression" title=" multiple regression"> multiple regression</a> </p> <a href="https://publications.waset.org/abstracts/185886/a-study-of-user-awareness-and-attitudes-towards-civil-id-authentication-in-omans-electronic-services" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185886.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">57</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">7197</span> A Preliminary Study of the Subcontractor Evaluation System for the International Construction Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hochan%20Seok">Hochan Seok</a>, <a href="https://publications.waset.org/abstracts/search?q=Woosik%20Jang"> Woosik Jang</a>, <a href="https://publications.waset.org/abstracts/search?q=Seung-Heon%20Han"> Seung-Heon Han</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The stagnant global construction market has intensified competition since 2008 among firms that aim to win overseas contracts. Against this backdrop, subcontractor selection is identified as one of the most critical success factors in overseas construction project. However, it is difficult to select qualified subcontractors due to the lack of evaluation standards and reliability. This study aims to identify the problems associated with existing subcontractor evaluations using a correlations analysis and a multiple regression analysis with pre-qualification and performance evaluation of 121 firms in six countries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=subcontractor%20evaluation%20system" title="subcontractor evaluation system">subcontractor evaluation system</a>, <a href="https://publications.waset.org/abstracts/search?q=pre-qualification" title=" pre-qualification"> pre-qualification</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20evaluation" title=" performance evaluation"> performance evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation%20analysis" title=" correlation analysis"> correlation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression%20analysis" title=" multiple regression analysis"> multiple regression analysis</a> </p> <a href="https://publications.waset.org/abstracts/65032/a-preliminary-study-of-the-subcontractor-evaluation-system-for-the-international-construction-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65032.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">368</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">7196</span> A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Wickramarachchi">M. S. Wickramarachchi</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20S.%20Nawarathna"> L. S. Nawarathna</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20M.%20B.%20Dematawewa"> C. M. B. Dematawewa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification%20models" title="classification models">classification models</a>, <a href="https://publications.waset.org/abstracts/search?q=egg%20weight" title=" egg weight"> egg weight</a>, <a href="https://publications.waset.org/abstracts/search?q=fertilised%20eggs" title=" fertilised eggs"> fertilised eggs</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a> </p> <a href="https://publications.waset.org/abstracts/160981/a-statistical-approach-to-predict-and-classify-the-commercial-hatchability-of-chickens-using-extrinsic-parameters-of-breeders-and-eggs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160981.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">87</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">7195</span> Multiple Linear Regression for Rapid Estimation of Subsurface Resistivity from Apparent Resistivity Measurements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabiu%20Bala%20Muhammad">Sabiu Bala Muhammad</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosli%20Saad"> Rosli Saad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=apparent%20resistivity" title="apparent resistivity">apparent resistivity</a>, <a href="https://publications.waset.org/abstracts/search?q=depth" title=" depth"> depth</a>, <a href="https://publications.waset.org/abstracts/search?q=horizontal%20location" title=" horizontal location"> horizontal location</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=true%20resistivity" title=" true resistivity"> true resistivity</a> </p> <a href="https://publications.waset.org/abstracts/70171/multiple-linear-regression-for-rapid-estimation-of-subsurface-resistivity-from-apparent-resistivity-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70171.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">7194</span> Statistical Model of Water Quality in Estero El Macho, Machala-El Oro</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rafael%20Zhindon%20Almeida">Rafael Zhindon Almeida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=statistical%20modeling" title="statistical modeling">statistical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20quality" title=" water quality"> water quality</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20components" title=" principal components"> principal components</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20models" title=" statistical models"> statistical models</a> </p> <a href="https://publications.waset.org/abstracts/176758/statistical-model-of-water-quality-in-estero-el-macho-machala-el-oro" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176758.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">98</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">7193</span> A Study of Anthropometric Correlation between Upper and Lower Limb Dimensions in Sudanese Population</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Altayeb%20Abdalla%20Ahmed">Altayeb Abdalla Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthropometry" title="anthropometry">anthropometry</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation" title=" correlation"> correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=limb" title=" limb"> limb</a>, <a href="https://publications.waset.org/abstracts/search?q=Sudanese" title=" Sudanese"> Sudanese</a> </p> <a href="https://publications.waset.org/abstracts/25051/a-study-of-anthropometric-correlation-between-upper-and-lower-limb-dimensions-in-sudanese-population" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25051.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">295</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">7192</span> Non-Methane Hydrocarbons Emission during the Photocopying Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kiurski%20S.%20Jelena">Kiurski S. Jelena</a>, <a href="https://publications.waset.org/abstracts/search?q=Aksentijevi%C4%87%20M.%20Sne%C5%BEana"> Aksentijević M. Snežana</a>, <a href="https://publications.waset.org/abstracts/search?q=Keci%C4%87%20S.%20Vesna"> Kecić S. Vesna</a>, <a href="https://publications.waset.org/abstracts/search?q=Oros%20B.%20Ivana"> Oros B. Ivana </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prosperity of electronic equipment in photocopying environment not only has improved work efficiency, but also has changed indoor air quality. Considering the number of photocopying employed, indoor air quality might be worse than in general office environments. Determining the contribution from any type of equipment to indoor air pollution is a complex matter. Non-methane hydrocarbons are known to have an important role of air quality due to their high reactivity. The presence of hazardous pollutants in indoor air has been detected in one photocopying shop in Novi Sad, Serbia. Air samples were collected and analyzed for five days, during 8-hr working time in three-time intervals, whereas three different sampling points were determined. Using multiple linear regression model and software package STATISTICA 10 the concentrations of occupational hazards and micro-climates parameters were mutually correlated. Based on the obtained multiple coefficients of determination (0.3751, 0.2389, and 0.1975), a weak positive correlation between the observed variables was determined. Small values of parameter F indicated that there was no statistically significant difference between the concentration levels of non-methane hydrocarbons and micro-climates parameters. The results showed that variable could be presented by the general regression model: y = b0 + b1xi1+ b2xi2. Obtained regression equations allow to measure the quantitative agreement between the variation of variables and thus obtain more accurate knowledge of their mutual relations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-methane%20hydrocarbons" title="non-methane hydrocarbons">non-methane hydrocarbons</a>, <a href="https://publications.waset.org/abstracts/search?q=photocopying%20process" title=" photocopying process"> photocopying process</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression%20analysis" title=" multiple regression analysis"> multiple regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=indoor%20air%20quality" title=" indoor air quality"> indoor air quality</a>, <a href="https://publications.waset.org/abstracts/search?q=pollutant%20emission" title=" pollutant emission"> pollutant emission</a> </p> <a href="https://publications.waset.org/abstracts/22642/non-methane-hydrocarbons-emission-during-the-photocopying-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22642.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">378</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">7191</span> The Effect of Peer Pressure and Leisure Boredom on Substance Use Among Adolescents in Low-Income Communities in Capetown</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaironeesa%20Hendricks">Gaironeesa Hendricks</a>, <a href="https://publications.waset.org/abstracts/search?q=Shazly%20Savahl"> Shazly Savahl</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Florence"> Maria Florence</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of the study is to determine whether peer pressure and leisure boredom influence substance use among adolescents in low-income communities in Cape Town. Non-probability sampling was used to select 296 adolescents between the ages of 16–18 from schools located in two low-income communities. The measurement tools included the Drug Use Disorders Identification Test, the Resistance to Peer Influence and Leisure Boredom Scales. Multiple regression revealed that the combined influence of peer pressure and leisure boredom predicted substance use, while peer pressure emerged as a stronger predictor than leisure boredom on substance use among adolescents. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=substance%20use" title="substance use">substance use</a>, <a href="https://publications.waset.org/abstracts/search?q=peer%20pressure" title=" peer pressure"> peer pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=leisure%20boredom" title=" leisure boredom"> leisure boredom</a>, <a href="https://publications.waset.org/abstracts/search?q=adolescents" title=" adolescents"> adolescents</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20regression" title=" multiple regression"> multiple regression</a> </p> <a href="https://publications.waset.org/abstracts/17384/the-effect-of-peer-pressure-and-leisure-boredom-on-substance-use-among-adolescents-in-low-income-communities-in-capetown" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17384.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">598</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">7190</span> A Comparison of Smoothing Spline Method and Penalized Spline Regression Method Based on Nonparametric Regression Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autcha%20Araveeporn">Autcha Araveeporn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20regression%20model" title="nonparametric regression model">nonparametric regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20spline%20regression%20method" title=" penalized spline regression method"> penalized spline regression method</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20spline%20method" title=" smoothing spline method"> smoothing spline method</a>, <a href="https://publications.waset.org/abstracts/search?q=Stock%20Exchange%20of%20Thailand%20%28SET%29" title=" Stock Exchange of Thailand (SET)"> Stock Exchange of Thailand (SET)</a> </p> <a href="https://publications.waset.org/abstracts/2974/a-comparison-of-smoothing-spline-method-and-penalized-spline-regression-method-based-on-nonparametric-regression-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2974.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">439</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">7189</span> Determining the Causality Variables in Female Genital Mutilation: A Factor Screening Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ekele%20Alih">Ekele Alih</a>, <a href="https://publications.waset.org/abstracts/search?q=Enejo%20Jalija"> Enejo Jalija</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Female Genital Mutilation (FGM) is made up of three types namely: Clitoridectomy, Excision and Infibulation. In this study, we examine the factors responsible for FGM in order to identify the causality variables in a logistic regression approach. From the result of the survey conducted by the Public Health Division, Nigeria Institute of Medical Research, Yaba, Lagos State, the tau statistic, τ was used to screen 9 factors that causes FGM in order to select few of the predictors before multiple regression equation is obtained. The need for this may be that the sample size may not be able to sustain having a regression with all the predictors or to avoid multi-collinearity. A total of 300 respondents, comprising 150 adult males and 150 adult females were selected for the household survey based on the multi-stage sampling procedure. The tau statistic, <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=female%20genital%20mutilation" title="female genital mutilation">female genital mutilation</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20regression" title=" logistic regression"> logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=tau%20statistic" title=" tau statistic"> tau statistic</a>, <a href="https://publications.waset.org/abstracts/search?q=African%20society" title=" African society"> African society</a> </p> <a href="https://publications.waset.org/abstracts/75290/determining-the-causality-variables-in-female-genital-mutilation-a-factor-screening-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75290.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">7188</span> The Relationship between Iranian EFL Learners' Multiple Intelligences and Their Performance on Grammar Tests</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rose%20Shayeghi">Rose Shayeghi</a>, <a href="https://publications.waset.org/abstracts/search?q=Pejman%20Hosseinioun"> Pejman Hosseinioun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learner-centered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiple%20intelligence" title="multiple intelligence">multiple intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=grammar" title=" grammar"> grammar</a>, <a href="https://publications.waset.org/abstracts/search?q=ELT" title=" ELT"> ELT</a>, <a href="https://publications.waset.org/abstracts/search?q=EFL" title=" EFL"> EFL</a>, <a href="https://publications.waset.org/abstracts/search?q=TIMI" title=" TIMI"> TIMI</a> </p> <a href="https://publications.waset.org/abstracts/34916/the-relationship-between-iranian-efl-learners-multiple-intelligences-and-their-performance-on-grammar-tests" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34916.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">490</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">7187</span> Machine Vision System for Measuring the Quality of Bulk Sun-dried Organic Raisins</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navab%20Karimi">Navab Karimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Tohid%20Alizadeh"> Tohid Alizadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sun-dried%20organic%20raisin" title="sun-dried organic raisin">sun-dried organic raisin</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=ann%20regression" title=" ann regression"> ann regression</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20regression" title=" linear regression"> linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a>, <a href="https://publications.waset.org/abstracts/search?q=south%20azerbaijan." title=" south azerbaijan."> south azerbaijan.</a> </p> <a href="https://publications.waset.org/abstracts/172004/machine-vision-system-for-measuring-the-quality-of-bulk-sun-dried-organic-raisins" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172004.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">73</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">7186</span> A Kolmogorov-Smirnov Type Goodness-Of-Fit Test of Multinomial Logistic Regression Model in Case-Control Studies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen%20Li-Ching">Chen Li-Ching </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case-control%20studies" title="case-control studies">case-control studies</a>, <a href="https://publications.waset.org/abstracts/search?q=goodness-of-fit%20test" title=" goodness-of-fit test"> goodness-of-fit test</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov-Smirnov%20test" title=" Kolmogorov-Smirnov test"> Kolmogorov-Smirnov test</a>, <a href="https://publications.waset.org/abstracts/search?q=multinomial%20logistic%20regression" title=" multinomial logistic regression"> multinomial logistic regression</a> </p> <a href="https://publications.waset.org/abstracts/44967/a-kolmogorov-smirnov-type-goodness-of-fit-test-of-multinomial-logistic-regression-model-in-case-control-studies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44967.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">7185</span> The Influence of Interest, Beliefs, and Identity with Mathematics on Achievement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Asma%20Alzahrani">Asma Alzahrani</a>, <a href="https://publications.waset.org/abstracts/search?q=Elizabeth%20Stojanovski"> Elizabeth Stojanovski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mathematics%20achievement" title="Mathematics achievement">Mathematics achievement</a>, <a href="https://publications.waset.org/abstracts/search?q=math%20efficacy" title=" math efficacy"> math efficacy</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematics%20interest" title=" mathematics interest"> mathematics interest</a>, <a href="https://publications.waset.org/abstracts/search?q=factors%20influence" title=" factors influence"> factors influence</a> </p> <a href="https://publications.waset.org/abstracts/117253/the-influence-of-interest-beliefs-and-identity-with-mathematics-on-achievement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117253.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">150</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">7184</span> An Overbooking Model for Car Rental Service with Different Types of Cars</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Naragain%20Phumchusri">Naragain Phumchusri</a>, <a href="https://publications.waset.org/abstracts/search?q=Kittitach%20Pongpairoj"> Kittitach Pongpairoj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=overbooking" title="overbooking">overbooking</a>, <a href="https://publications.waset.org/abstracts/search?q=car%20rental%20industry" title=" car rental industry"> car rental industry</a>, <a href="https://publications.waset.org/abstracts/search?q=revenue%20management" title=" revenue management"> revenue management</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20model" title=" stochastic model"> stochastic model</a> </p> <a href="https://publications.waset.org/abstracts/77611/an-overbooking-model-for-car-rental-service-with-different-types-of-cars" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77611.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">172</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=multiple%20regression&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=multiple%20regression&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=multiple%20regression&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=multiple%20regression&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=multiple%20regression&page=6">6</a></li> 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