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158 articles for “regression models”
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Research ArticleOpen accessIn the keywordsFuzzy Time Series: An Application to Tourism Demand ForecastingMuhammad Hisyam Lee, Maria Elena Nor, Suhartono et al.Problem statement: Forecasting is very important in many types of organizations since predictions of future events must be incorporated into the decision-making process. In the case of tourism demand, better forecast would help directors and investors make operational, tactical and strategic decisions. Besides that, government bodies need accurate tourism demand forecasts to plan required tourism infrastructures, such as accommodation site … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,478 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMoisture Content Prediction of Dried Longan Aril from Dielectric Constant Using Multilayer Perceptrons and Support Vector RegressionSanong Amaroek, Nipon Theera-Umpon, Kittichai Wantanajittikul, Sansanee AuephanwiriyakulProblem statement: Estimation of moisture contents of dried food products from their dielectric constants was an important step in moisture measurement systems. The regression models that provide good prediction performance are desirable. Approach: The Multilayer Perceptrons (MLP) and Support Vector Regression (SVR) were applied in this research to predict the moisture contents of dried longan arils from their dielectric constants. … …American Journal of Applied Sciences, Vol. 7, Issue 10 · 31 Oct 2010 · 7,668 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEffect of Impact Level and Fruit Properties on Golden Delicious Apple BruisingArzhang Javadi, Ebrahim Ahmadi, Mohammad Hossein Abbaspour-Fard et al.Problem Statement: Bruise damage is a major cause of fruit quality loss. Bruises occur under dynamic and static loading when stress induced in the fruit exceeds the failure stress of the fruit tissue. Statistical bruise estimation models were constructed to calculate Golden Delicious apple bruise volume with respect to fruit properties. Approach: The regression models were built based upon impact … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 2 · 30 Jun 2010 · 9,266 accessesView PDFCite
Research ArticleOpen accessIn the keywordsShort-Term and Medium-Term Load Forecasting for Jordan's Power SystemI. Badran, H. El-Zayyat, G. HalasaSeveral electric power companies are now forecasting electric loads based on conventional methods. However, since the relationship between loads and factors influencing these loads is nonlinear, it is difficult to identify its nonlinearity by using conventional methods. Most of papers deal with 24-h-ahead load forecasting or next day peak load forecasting. These methods forecast the demand power by using forecasted … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 7,083 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDevelopment of Software Reliability Growth Models for Industrial Applications Using Fuzzy LogicSultan AljahdaliProblem statement: The utilization of Software Reliability Growth Models (SRGM) plays a major role in monitoring progress, accurately predicting the number of faults in the software during both development and testing processes; define the release date of a software product, helps in allocating resources and estimating the cost for software maintenance. This leads to achieving the required reliability level of … …Journal of Computer Science, Vol. 7, Issue 10 · 9 Aug 2011 · 7,008 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOn Calculating the Hougaard Measure of Skewness in a Nonlinear Regression Model with Two ParametersS. A. EL-ShehawyProblem statement: This study presented an alternative computational algorithm for determining the values of the Hougaard measure of skewness as a nonlinearity measure in a Nonlinear Regression model (NLR-model) with two parameters. Approach: These values indicated a degree of a nonlinear behavior in the estimator of the parameter in a NLR-model. Results: We applied the suggested algorithm on an example … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,163 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMacroeconomic Impact of Trade on Namibian Growth: An Empirical IllustrationCyril A. OgbokorThe study analyses the role of trade on the economy of Namibia by considering a different specification of the traditional export-growth model. Foreign direct investment is included to capture the potential effect of this variable on growth. Utilising a combination of bivariate and multivariate models, the researcher estimated the relationship between the selected macroeconomic variables used for the study. Macroeconomic … …Journal of Social Sciences, Vol. 1, Issue 1 · 31 Mar 2005 · 6,869 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Diagnosis of Parkinson's Disease Through Voice Analysis and Machine LearningAmrita Naik, Mohd Sahil Khan, Akhilesh Manoj Saraf et al.Parkinson’s Disease (PD) is a progressive neurological disorder, and its prevalence has increased considerably in recent years. Early and accurate diagnosis plays a crucial role in effective treatment, but identifying the disease in its early stages remains challenging, especially for non-specialist clinicians. This study presents a predictive analytics framework for detecting Parkinson's disease using voice-based features. To improve the diversity … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 652 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Based Prediction of Catch Yields in Small Scale FisheriesEpifelward Niño Olaivar Amora, Patrick D. CernaSmall-scale fisheries are critical for food security and livelihoods but increasingly face threats from overfishing and environmental change. This study employed machine learning to predict catch yields in Cogtong Bay, Philippines, using 3,478 records collected in 2020–2021 that included species, gear, location, season, and weather data. Models developed in Python with scikit-learn and XGBoost compared Random Forest (RF), Extreme Gradient … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 638 accessesView PDFCite