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50 results for “Regression Modeling”
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Research ArticleOpen accessIn the keywordsLinear Genetic Programming for Prediction of Nickel Recovery from Spent Nickel CatalystMona E. Ossman, Walaa Sheta, Y. EltaweelProblem statement: In this study Linear Genetic Programming (LGP) and statistical regression are used in predicting Current Efficiency (CE) of Electro deposition cell used for recovery of nickel from spent nickel catalyst. Approach: The Nickel electro deposition from spent catalyst leachate solutions was studied to determine the effect of the operative conditions such as nickel concentration, temperature, current density and … …American Journal of Engineering and Applied Sciences, Vol. 3, Issue 2 · 30 Jun 2010 · 8,345 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnchoring 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 PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of Physicochemical Parameters in a Rainwater Harvesting and Treatment System Modeled Using the Yahtun Algorithm in Native Communities of Northern PeruEli Morales-Rojas, Edwin Adolfo Díaz Ortiz, José Emmanuel Cruz de La Cruz et al.The inhabitants of the native communities of northern Peru do not have drinking water systems, generating serious health impacts. In this sense, rainwater harvesting systems have become an alternative for these areas. Therefore, the objective of this study was to predict the physicochemical parameters in a rainwater collection and treatment system, modeled by means of a novel “Yahtun” algorithm. The … …OnLine Journal of Biological Sciences, Vol. 25, Issue 1 · 13 Feb 2025 · 5,149 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring University Students' Perceptions of AI Tools in Programming Education: An Extended TAM ApproachAreej Abdullah AlfuhaidGenerative Artificial Intelligence (AI) is commonly used in programming education. Tools such as ChatGPT and GitHub Copilot aid in code generation, debugging, and explanation. The benefits are clear, though concerns about learning quality and academic integrity persist.We tested an extended Technology Acceptance Model (TAM) for university programming courses. The model included perceived usefulness and perceived ease of use. It added … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 2,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractSemSimp: A Parametric Method for Evaluating the Semantic Similarity of Digital ResourcesAntonio De Nicola, Anna Formica, Ida Mele, Francesco TaglinoAbioui, H., Idarrou, A., Bouzit, A., & Mammass, D. (2018). Towards a Novel and Generic Approach for OWL Ontology Weighting. Procedia Computer Science, 127, 426–435. https://doi.org/10.1016/j.procs.2018.01.140 Adhikari, A., Dutta, B., Dutta, A., Mondal, D., & Singh, S. (2018). An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. Journal of the Association for … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractCalculation of the Hubble Constant, the Minimum Mass and the Proton Charge Radius Using the Dirac's Hypothesis on the Ratio of the Electrostatic Force to the Gravitational ForcePaul TalbotAtoui, M., Barbaro, M. B., Hoballah, M., Keyrouz, C., Lassaut, M., Marchand, D., Quéméner, G., & Voutier, E. (2023). Determination of the Moments of the Proton Charge Density. ArXiv, 13521. https://doi.org/10.48550/arXiv.2304.13521 Berman, M. S. (1992). Large Number Hypothesis. International Journal of Theoretical Physics, 31, 1447–1450. https://doi.org/10.1007/bf00673977 Beyer, A., Maisenbacher, L., Matveev, A., Pohl, R., Khabarova, K., Grinin, A., Lamour, T., … …Physics International, Vol. 14, Issue 1 · 2 Sep 2023 · 9,106 accessesView PDFCite
Review ArticleOpen accessIn the abstractReview of Zero-Inflated Models with Missing DataT. Martin Lukusa, Shen-Ming Lee, Chin-Shang LiThe literature of count regression models covers a large scope of studies and applications that implemented simple and standard models for count response variables by using Poisson regression models, binomial regression models, negative binomial regression models, geometric regression models, or generalized Poisson regression models. These regression models have received considerable attention in various situations. Nevertheless in many fields, the distribution … …Current Research in Biostatistics, Vol. 7, Issue 1 · 31 Oct 2017 · 14,406 accessesView PDFCite
Research ArticleOpen accessIn the abstractBuilding Energy Modeling Using Artificial Neural NetworksMaya Arida, Nabil Nassif, Rand Talib, Taher Abu-LebdehAccurate modeling of total building energy is now vital to reduce energy consumption. This is especially true for buildings since they are considered as the largest energy consumer in the United States. This paper investigates modeling methods for building energy-systems using non-linear auto-regression artificial neural networks. The proposed model can forecast the whole building energy consumptions given the four input … …Energy Research Journal, Vol. 7, Issue 2 · 6 Jun 2017 · 7,125 accessesView PDFCite