48 articles for “Error Accuracy Prediction”

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Research ArticleOpen accessIn the abstractANN Based Prediction of Effect of Reinforcements on Abrasive Wear Loss and Hardness in a Hybrid MMCP. Sathyabalan, V. Selladurai, P. SakthivelProblem statement: The reinforcements added to an alloy lead to variation in properties. The content and size of the reinforcement influences the properties of composites. Very little research has been carried out in hybrid composites. Work on hybrid LM6 aluminium alloy metal matrix composites (MMC) with flyash and SiC has been initiated here. The effect of the four parameters, size … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 7,551 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFine Needle Aspiration Cytology Evaluation for Classifying Breast Cancer Using Artificial Neural NetworkNor Ashidi Mat Isa, Esugasini Subramaniam, Mohd Yusoff Mashor, Nor Hayati OthmanThirteen cytology of fine needle aspiration image (i.e. cellularity, background information, cohesiveness, significant stromal component, clump thickness, nuclear membrane, bare nuclei, normal nuclei, mitosis, nucleus stain, uniformity of cell, fragility and number of cells in cluster) are evaluated their possibility to be used as input data for artificial neural network in order to classify the breast precancerous cases into four … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 7,152 accessesView PDF Cite

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 · 6,941 accessesView PDF Cite

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 · 6,857 accessesView PDF Cite

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 · 7,822 accessesView PDF Cite

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 · 632 accessesView PDF Cite

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 · 1,355 accessesView PDF Cite

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 · 7,533 accessesView PDF Cite