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389 results for “Prediction Model”
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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 · 6,469 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 494 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 · 2,120 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 422 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting the Number of Monthly Active Facebook and Twitter Worldwide Users Using ARMA ModelQasem Abu Al-Haija, Qian Mao, Kamal Al NasrIn this study, an Auto-Regressive Moving Average (ARMA) Model with optimal order has been developed to estimate and forecast the short term future numbers of the monthly active Facebook and Twitter worldwide users. In order to pickup the optimal estimation order, we analyzed the model order vs. the corresponding model error in terms of final prediction error. The simulation results … …Journal of Computer Science, Vol. 15, Issue 4 · 19 Apr 2019 · 8,607 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluating Patient Readmission Risk: A Predictive Analytics ApproachAvishek Choudhury, Dr. Christopher M. GreeneWith the emergence of the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services on October 1, 2012, forecasting unplanned patient readmission risk became crucial to the healthcare domain. There are tangible works in the literature emphasizing on developing readmission risk prediction models; However, the models are not accurate enough to be deployed in an actual clinical … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 7 Dec 2018 · 8,161 accessesView PDFCite
Research ArticleOpen accessIn the keywordsField Data Based Method for Predicting Long-Term SettlementsJianping Jiang, Qingsheng Chen, Sanjay NimbalkarThe estimation of the long-term foundation settlement in soft soil is very complex, which is attributed to a number of uncertainties associated with various factors, such as: (i) The compressibility parameters obtained in the laboratory from samples of relatively small size that are more homogeneous compared to heterogeneous field sediments in which various soil types may be interlayered at random … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 3 · 22 Feb 2016 · 8,255 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 · 8,218 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Fuzzy Based Mechanism For Allocation of Grid ResourcesM. Poonguzhali, S. ShanmugavelOne of the main challenges in Grid computing is efficient allocation of resources (CPU-hours, network bandwidth) to the tasks submitted by users. In our previous work a technique to allocate resources in a grid environment using predicted data has been proposed. We propose utilization of the predicted data the resources were classified into three types; they are permanent resources, semi-permanent … …Journal of Computer Science, Vol. 9, Issue 5 · 23 May 2013 · 6,777 accessesView PDFCite
Research ArticleOpen accessIn the keywordsContext Aware Middleware Model for Handling Vehicular Safety IssuesArunkumar Thangavelu, R. A.K. SaravanaguruProblem statement: This study proposed a mathematical model for the existing framework InVANET; context prediction and simulation for vehicle safety. Approach: Markov process was used to model context and predict the states with the help of transition probability matrix. The context parameters were collected from CarSim simulator and inferred using JENA and SPARQL. Results: The longitudinal speed and lateral offset … …Journal of Computer Science, Vol. 8, Issue 8 · 12 Jul 2012 · 7,105 accessesView PDFCite