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48 results for “Error Accuracy Prediction”
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Research ArticleOpen accessIn the abstractIntelligence 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 · 6,947 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Application of Carhart Atom Pairs to Predict Anticonvulsant ActivityAlan Talevi, Julian J. Prieto, Luis E. Bruno-Blanch, Eduardo CastroAbout 50 million people in the world suffer from epilepsy, especially in childhood, adolescence and old age. Available treatment fails to control epilepsy in up to 30% of affected people. In developing countries, however, the amount of patients that do not receive adequate treatment climbs up to 75%. Moreover, the new generation of antiepileptic drugs (AEDs) causes important central and … …American Journal of Biochemistry and Biotechnology, Vol. 2, Issue 3 · 30 Sep 2006 · 6,862 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Models for Hardened Properties of Self-Compacting ConcreteArabi N.S. Al Qadi, Kamal Nasharuddin Bin Mustapha, Hashem Al-Mattarneh, Qahir N.S. AL-KadiProblem statement: For predicting workability and hardened properties of Self-Compacting Concrete (SCC) no well known explicit formulation. Approach: Statistical models were carried out to model the influence of key mixture parameter (cement, water to powder ratio, fly ash and super plasticizer) on hardened properties affecting the performance of SCC. Such responses included compressive strength at 3, 7 and 28 days … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 8,148 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdjustment of Peak Streamflows of a Tropical River for UrbanizationAta Amini, Thamer Mohammad Ali, Abdul Halim B Ghazali, Bujang Kim HuatPeak runoff from a catchment is influenced by many factors such as intensity and duration of rainfall, catchment topography, catchment shape, land use and other variables. For a particular catchment, landuse change and other human activities will alter the characteristic of catchment hydrograph. Problem statement: As a result of urbanization, the magnitude of floods occurring in a catchment increased. It … …American Journal of Environmental Sciences, Vol. 5, Issue 3 · 30 Jun 2009 · 7,550 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Efficient Finite Element Software of Crack Propagation Simulation using Adaptive Mesh StrategyAbdulnaser M. Alshoaibi, A. K. Ariffin, M. N. AlmaghrabiThe purpose of this study is on the determination of 2D crack paths and surfaces as well as on the evaluation of the stress intensity factors as a part of the damage tolerant assessment. Problem statement: The evaluation of SIFs and crack tip singular stresses for arbitrary fracture structure are a challenging problem, involving the calculation of the crack path … …American Journal of Applied Sciences, Vol. 6, Issue 4 · 30 Apr 2009 · 7,830 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnchoring 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
Research ArticleOpen accessAll words, across the recordDeep 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 · 1,363 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPredicting Packet Transmission Data over IP Networks Using Adaptive Neuro-Fuzzy Inference SystemsSamira Chabaa, Abdelouhab ZeroualProblem statement: The statistical modeling for predicting network traffic has now become a major tool used for network and is of significant interest in many domains: Adaptive application, congestion and admission control, wireless, network management and network anomalies. To comprehend the properties of IP-network traffic and system conditions, many kinds of reports based on measured network traffic data have been … …Journal of Computer Science, Vol. 5, Issue 2 · 28 Feb 2009 · 7,535 accessesView PDFCite