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Research ArticleOpen accessPhrase in the titleHybridization of Neural Learning Algorithms Using Evolutionary and Discrete Gradient ApproachesRanadhir Ghosh, John Yearwood, Moumita Ghosh, Adil BagirovIn this study we investigated a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 6,587 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDengue Fever Prediction Empowered by Radial Basis Function Networks, Dynamic Mode Decomposition, and Learning-Based Foraging AlgorithmArchana T, Faritha Banu JDengue fever is presently considered a major health threat that must be addressed. External and internal factors that induce nonlinear oscillations in the occurrence of dengue disease have made optimal resource allocation stimulating. Public health initiatives aimed at eradicating this vector use accurate and timely data through field processes. In dengue-endemic nations, early dengue prediction remains a main concern for … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 1,496 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired AlgorithmsIndira Priyadarsini, I.S. Siva Rao, P. Swetha et al.This study presents a novel approach for early prediction of heart disease using bio-inspired optimization algorithms to select and optimize features. The proposed approach utilizes a Genetic Algorithm (GA), Bat Algorithm (BA), Bee Algorithm (BA), and Ant Colony Optimization (ACO) to optimize a set of four features for improved prediction accuracy. The optimization process aims to identify the most relevant … …Journal of Computer Science, Vol. 21, Issue 1 · 4 Dec 2024 · 5,227 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,208 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Enhanced Dynamic Source Routing Algorithm for the Mobile Ad-Hoc Network using Reinforcement learning under the COVID-19 ConditionsEhsan Moqimi, Amir Najafi, Mojtaba AjamiToday, the use of computer networks is evident in all walks of life, including mobile phones, vehicles, personal computers, the workplace and more. Creating and operating networks between each of the above-mentioned devices require good infrastructure to be able to communicate between these devices. To solve this problem, there were networks called ad-hoc networks, which were able to network with … …Journal of Computer Science, Vol. 16, Issue 10 · 31 Oct 2020 · 6,994 accessesView PDFCite
InvestigationOpen accessEvery word in the titleA Conceptualization of Distributed Computation for Machine Learning: The Voting AlgorithmTalal Talib JameelThis paper describes a voting algorithm that can be used to find the most optimal solution to clustering problems in machine learning. As part of the family of algorithms known as Condorcet methods, the voting algorithm is used to choose a particular candidate, even in the absence of a definitive majority. The algorithm proceeds in two steps: Renormalization and reconciliation. … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 2 Mar 2017 · 7,890 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImplementation of an Improved Data Encryption Algorithm in a Web Based Learning SystemAdeolu Olabode Afolabi, Rotimi AdagunodoProblem statement: This study proffered solution to some identified data insecurity problems in software development by the use of Web-based learning system as a test bed and development of an hybrid crypto-biometric security system. Approach: A variant of data encryption algorithm tagged (XOR-RSA algorithm) is developed in order to encrypt the messages being sent between the learner and the facilitator. … …Physics International, Vol. 2, Issue 1 · 23 Jan 2012 · 7,768 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Innovative Method for Recognizing Face Expressions Based on Genetic Algorithm and Extreme Learning Based Hybrid ModelTushar Dhar Shukla, Md Oqail Ahmad, Puneet Sapra et al.The detection of facial action coding system Action Units (AU) and other facial expressions has been a major focus of computer science for more than 20 years categorizing discrete emotional states based on facial expressions. While several widely used face expression databases exist, standardization and comparability remain key challenges. The lack of a universally recognized assessment procedure and insufficient information … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 7,293 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Algorithm for Earthquake Prediction Using Machine Learning MethodsNada Badr Jarah, Abbas Hanon Hassin Alasadi, Kadhim Mahdi HashimSeismic tremors are among the foremost perilous normal fiascos individuals confront due to their event without earlier caution and their effect on their lives and properties. In expansion, to consider future disaster prevention measures for major earthquakes, it is necessary to predict earthquakes using Neural Networks (NN). A machine learning technique has developed a technology to predict earthquakes from ground … …Journal of Computer Science, Vol. 20, Issue 2 · 23 Dec 2023 · 7,079 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance 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