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203 results for “Prediction Models”
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Research ArticleOpen accessEvery word in the titleComparison of Multiple Linear Regression and Neural Network Models in Bank Performance Prediction in BotswanaHassan Kablay, Victor GumboBank performance is critical to the banking sector and the economy as a whole. In this study, Multiple Linear Regression (MLR) technique and feed forward Neural Network (NN) are used to predict the performance of 11 banks in Botswana. Return on Assets (RoA) is used as the dependent variable, while management quality, credit risk, liquidity, financial leverage and capital adequacy … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 10 Jan 2022 · 6,465 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 accessIn the keywordsDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHMGD: A High-Accuracy Model for Detection and Prediction of Respiratory Genetic DiseasesKamal ElDahshan, Hesham Hefny, Iman Ahmed ElSayedRespiratory genetic diseases are considered a major participant in the reasons of death worldwide nowadays and were one of the major participants in helping in increasing the numbers of COVID-19 patients. It is considered one of the most alarming diseases affecting in particular the respiratory system. The journey of early detection of respiratory genetic diseases is considered to be very … …Journal of Computer Science, Vol. 20, Issue 6 · 30 Mar 2024 · 5,272 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEMPIRICAL COMPARISON OF TWO METRICS SUITES FOR MAINTAINABILITY PREDICTION IN PACKAGES OF OBJECT-ORIENTED SYSTEMS: A CASE STUDY OF OPEN SOURCE SOFTWAREK.G. MadhwarajSoftware maintainability has been an important external quality attribute that concerns both styles of software development, the proprietary model as well as open source. As lots of open source software are predominantly built using the OO paradigm, there exists a need for empirical validation with respect to certain quality aspects especially maintainability. There are a few studies in the past … …Journal of Computer Science, Vol. 10, Issue 11 · 10 Dec 2014 · 8,213 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIntelligence System for Software Maintenance Severity PredictionParvinder Singh Sandhu, Sunil Kumar, Hardeep SinghThe software industry has been experiencing a software crisis, a difficulty of delivering software within budget, on time, and of good quality. This may happen due to number of defects present in the different modules of the project that may require maintenance. This necessitates the need of predicting maintenance urgency of the particular module in the software. In this paper, … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,941 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 accessesView PDFCite
Review ArticleOpen accessIn the keywordsA Systematic Review Regarding the Prediction of Academic PerformancePercy De-La-Cruz, Rommel Rojas-Coaquira, Hugo Vega-Huerta et al.The prediction of students' academic performance is an area of great concern for universities and educational institutions since academic performance is one of the most important aspects of the learning process. To analyze this behavior, this study makes a critical analysis of the topic of interest and aims to review, analyze and summarize the latest research advances related to the … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 8,602 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPrediction of Grain Products in TurkeyÖzlem Akay, Gökmen Bozkurt, Güzin YükselMarketing of agricultural products starts with the planning of production on the farm and ends with the sale of food or other goods to manufacturers or consumers. Overall, marketing is a main part of successful agriculture but its significance is usually underestimated, particularly in developing countries. In Turkey, annual variations in grain production are reasonable and result primarily from changes … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 10 Jul 2017 · 7,322 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite