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159 results for “regression models”
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Research ArticleOpen accessIn the abstractComparative Analysis of the Efficacy of Landslide Susceptibility ModelsJordan Henrique de Souza, Gislaine dos Santos, Gabriela Guimarães Gouvêa de Oliveira et al.This research aims to analyze the efficacy of SHALSTAB, IPT, SAGA, SMORPH and modified SMORPH models in evaluating landslide susceptibility. Statistical analysis concerning both the efficacy of the models in the prediction of landslide risks and the concordance between the models according to landslide occurrence or non-occurrence was performed. For this work, logistic regression, Receiver Operating Characteristic (ROC) curves, Kappa … …American Journal of Environmental Sciences, Vol. 15, Issue 3 · 31 May 2019 · 8,839 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplications of Machine Learning in Building Energy Prediction and SavingsPriyan Rai, Dr. Nabil Nassif, Kevin Eaton, Alexander RodriguesIn a constantly advancing world with growing needs, buildings play in important role in the daily functioning of the society. Developing more and more advanced techniques to optimize the working of these buildings is highly important for a constant growth. Modern computational techniques have opened doors to create advanced models that can utilize efficient techniques to produce highly accurate results. … …Energy Research Journal, Vol. 10, Issue 1 · 15 Mar 2019 · 8,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractSubset ARMA Model Identification for Monthly Electricity Consumption DataAmaal El Sayed Abd El Ghany MubarakSubset models can always be highly influential in series analysis, particularly when the data demonstrate a sort of form in periodic behavior with miscellaneous natural period's ranges, specifically; days, weeks, months and years. Subset models can also be effective as they let the number of parameters lower allowing only the really needed ones to be present in the model. Though … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Mar 2019 · 7,140 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Review ArticleOpen accessIn the abstractVisualization of Data Mining Techniques for the Prediction of Breast Cancer with High Accuracy RatesVasudev Sharma, Raj Kumar Rajasekaran, Shreya BadhrinarayananBreast cancer is one of the leading causes of death in women worldwide. Around one in 30 women are affected by breast cancer. Mammography has helped in detecting breast cancer in the early stages which have reduced mortality. The diagnosis of breast cancer is dependent on a variety of parameters. In this paper, we aim to create the best model … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 8,948 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence and Mathematical Modelling-Based Techniques to Improve Social Media MarketingKiran Chaudhary, Mohammad Naquibur Rahman, Nabeela Hasan et al.The Businessperson is using social media to do marketing of their product. Almost all people use social media. Most people relate to social media. Social media marketing is beneficial in making the product more popular and easy ways to introduce the product to everyone in economical ways. In this study, we introduce the concept of machine learning and mathematical models … …Journal of Computer Science, Vol. 21, Issue 1 · 5 Dec 2024 · 5,478 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 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 abstractArtificial Intelligence in COVID-19 Management: A Systematic ReviewSamaneh Mohammadi, SeyedAhmad SeyedAlinaghi et al.With the development of modern technologies in the field of healthcare, the use of Artificial Intelligence (AI) in disease management is increasing. AI methods may assist healthcare providers in the COVID-19 era. The current study aimed to observe the efficacy and importance of AI for managing the COVID-19 pandemic. An organized search was conducted, utilizing PubMed, Web of Science, Scopus, … …Journal of Computer Science, Vol. 19, Issue 5 · 30 Mar 2023 · 8,052 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