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389 results for “Prediction Model”
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Research ArticleOpen accessEvery word in the titleHouse Price Prediction: Hedonic Price Model vs. Artificial Neural NetworkVisit Limsombunchai, Christopher Gan, Minsoo LeeThe objective of this study is to empirically compare the predictive power of the hedonic model with an artificial neural network model for house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 9,603 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePost-COVID Impact Analysis and Effective Recommendation Solutions Over Risk Prediction Using Hybrid ModelBoddeti Jaggan Mohan Ravi Kumar, P. V. G. D. Prasad Reddy, G SrinivasThe COVID-19 pandemic (2019-2022) resulted in significant global mortality, largely attributed to the virus's unpredictable pathophysiology, rapid disease progression affecting multiple organ systems, and initial lack of effective treatments. This study systematically examines post-COVID-19 complications across major organ systems, including respiratory dysfunction, cardiovascular complications, renal disorders, musculoskeletal pain, gastrointestinal disturbances, neurological sequelae, alopecia, endocrine and metabolic dysregulation, and mental health … …Journal of Computer Science, Vol. 21, Issue 11 · 23 Dec 2025 · 1,643 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhancing Electric Vehicle Charging Demand Prediction Using a Novel SAE-DNN Neural Network Model for Probabilistic ForecastingNaga Raju Hari Manikyam, A. Thangam, J. Murugachandravel et al.The rapid growth and widespread adoption of Electric Vehicles (EVs) play a crucial role in the progress of intelligent transportation systems, resulting in a significant decrease in environmentally damaging greenhouse gas emissions. The increase in EV usage has made it crucial to develop charging infrastructure to keep up with the growing demand. Precisely predicting EV charging demand is crucial to … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,536 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA TIME-DELAY CASCADING NEURAL NETWORK ARCHITECTURE FOR MODELING TIME-DEPENDENT PREDICTOR IN ONSET PREDICTIONAgus Buono, Imas Sukaesih Sitanggang, Mushthofa, Aziz KustiyoThe occurrence of rain before the real start of a rainy season often mislead farmers into thinking that rainy season has started and suggesting them to start planting immediately. In reality, rainy season has not started yet, causing the already-planted rice seed to experience dehydration. Therefore, a model that can predict the onset of rainy season is required, so that … …Journal of Computer Science, Vol. 10, Issue 6 · 29 Jan 2014 · 6,647 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Fuzzy Petri-Net Based Conceptual Model for Risk Prediction in Enterprise Resource Planning Acquisition Decisions for Small and Medium EnterprisesVijayakumar Bharathi, Dhanya Pramod, Ramakrishnan RamanThis study identifies and evaluates certain critical pitfalls in the acquisition phase of ERP adoption in Small and Medium Enterprises (SMEs) and develops a model for evaluating the risk of failure. On the acquisition stage a set of risks has been identified based on past research work and each of these risks have been explained through a set of well-defined … …Journal of Computer Science, Vol. 9, Issue 1 · 18 Mar 2013 · 7,073 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConsumer Choice Prediction: Artificial Neural Networks versus Logistic ModelsChristopher Gan, Visit Limsombunchai, Mike Clemes, Amy WengConventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. The purpose of this paper is to empirically compare the predictive power of the probability neural … …Journal of Social Sciences, Vol. 1, Issue 4 · 31 Dec 2005 · 8,441 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAerodynamic Noise Prediction Using stochastic Turbulence ModelingArash Ahmadzadegan, Mehran TadjfarAmongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field). A simple and … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,223 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePrediction and Analysis of COVID-19 Cases using Regression Models: A Descriptive Case Study of IndiaIsmail KeshtaThe Coronavirus(SARS-CoV-2) is a respiratory illness that emerged in Wuhan, China, on December31, 2019, according to reports by the World Health Organization (WHO). Hospitalrecords in India indicate that COVID-19 hospitalizations in the second wave ofCOVID-19 more than doubled those in the first wave. Limited studies have beenconducted to establish the extent to which the second wave of COVID-19increased the infection … …Journal of Computer Science, Vol. 18, Issue 10 · 12 Oct 2022 · 6,156 accessesView PDFCite