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35 results for “Support Vector Regression”
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Research ArticleOpen accessIn the abstractCooling Load Prediction in the Under-Actuated Zone with Multilayer Perceptron Artificial Neural NetworkYaddarabullah, Aedah Abd Rahman, Amna SaadThis study focuses on addressing the challenge of predicting cooling loads in under-actuated zones, where the variability in occupant behavior, environmental conditions, and electronic usage creates complex dynamics. Traditional models like Support Vector Regression (SVR) and E-Lastic-Net (ELN) often struggle to capture these non-linear relationships, leading to inefficient Heating, Ventilation, and Air Conditioning (HVAC) management and increased energy consumption. To … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 5,300 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Disease Index Based on Multi-Spectra of UAV to Estimate Cotton DiseaseBing Chen, Jing Wang, Qiong Wang et al.Verticillium wilt is a significant disease that affects cotton plants, which can lead to stunted growth and reduced yield. To address this, a multi-spectral comprehensive monitoring disease index model is developed using an Unmanned Aerial Vehicle (UAV) to monitor the severity of cotton Verticillium wilt. First, multi-spectral dates were collected from Hexacopter (HY-6X) and the phenotype disease grade of cotton … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 25 Mar 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Machine Learning-Based Algorithms to Predict the Early Childhood Development Among Under Five Children in BangladeshMd. Ismail Hossain, Iqramul Haq, Ashis Talukder et al.In this research, an effort has been made to apply a number of classifiers to predict Early Child Development (ECD) in the context of Bangladesh using the Bangladesh multiple indicator cluster survey, 2019 data set (i.e., to evaluate which sort of algorithm best identifies ECDI). To predict the ECD, nine well-known machine learning algorithms were applied, including Linear Regression (LR), … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 6,838 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
Research ArticleOpen accessIn the abstractBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,610 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Disease Prediction using Various Machine Learning AlgorithmsDebabrata Swain, Badal Parmar, Hansal Shah et al.Almostone-third of all deaths caused around the world were caused due tocardiovascular diseases. Even if death was not the result, much cost isincurred during the treatment of such diseases. But much of these deaths andtreatments could have been prevented with prior action. Advance knowledge ofthe symptoms and consequently proper care can lead us to avoid such diseases.Thus, current research proposes … …Journal of Computer Science, Vol. 18, Issue 10 · 13 Oct 2022 · 9,394 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite