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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 titleMapping Learning Algorithms on Data, a Useful Step for Optimizing Performances and Their ComparisonFilippo NeriIn this paper, we propose a novel methodology to map learning algorithms on data (performance map) in order to gain more insights into the distribution of their performances across their parameter space. This methodology provides useful information when selecting a learner's best configuration for the data at hand and it also enhances the comparison of learners across learning contexts. In … …Journal of Computer Science, Vol. 20, Issue 9 · 10 Jul 2024 · 4,501 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance Assessment of CPU Scheduling Algorithms: A Scenario-Based Approach with FCFS, RR, and SJFOlaa Hajjar, Escelle Mekhallalati, Nada Annwty et al.This study presents an extensive examination of CPU scheduling algorithms, focusing on the First-Come, First-Served (FCFS), Round-Robin (RR), and Shortest-Job-First (SJF) strategies through a carefully designed scenario-based approach. By deploying a Java-based simulation to dynamically generate random process arrival and burst times, this study simulates a variety of operational conditions to test these scheduling algorithms’ adaptability and performance in environments … …Journal of Computer Science, Vol. 20, Issue 9 · 16 Jun 2024 · 9,091 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance Analysis of Two Famous Cryptographic Algorithms on Mixed DataEmmanuel Abidemi Adeniyi et al.The rapid development of digital data sharing has made information security a crucial concern in data communication. The information security system heavily relies on encryption methods. These algorithms employ strategies to increase data secrecy and privacy by obscuring the information, which only those parties who have the accompanying key can decode or decrypt. Nevertheless, these methods also use a lot … …Journal of Computer Science, Vol. 19, Issue 6 · 29 May 2023 · 6,020 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCardiovascular 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 accessEvery word in the titlePerformance Optimization of Physics Simulations Through Genetic AlgorithmsOksana Shadura, Federico Carminati, Anatoliy PetrenkoThe GeantV R&D approach is revisiting the standard particle transport simulation approach to be able to benefit from “Single Instruction, Multiple Data” (SIMD) computational architectures or extremely parallel systems like coprocessors and GPUs. The goal of this work is to develop a mechanism for optimizing the programs used for High-Energy Physics (HEP) particle transport simulations using a “black-box” optimization approach. … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 8,091 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleApplications of Nature-Inspired Algorithms in Different Aspects of Semantic WebDeepika Chaudhary, Jaiteg Singh, D. P. KothariNature has always inspired us all the waggle dance of Honey bee, the school of whales and the swarm of ants, each element when observed carefully has the abundance of teachings. If we carefully observe nature, we find that although Nature seems to be very simple and systematic, it hides many complexities underneath it. As technology also follows the same … …Journal of Computer Science, Vol. 14, Issue 2 · 14 Feb 2018 · 8,760 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparison of Denoising Algorithms for Urban ScenesSamuel KozaitisSeveral new denoising algorithms have recently been presented that display comparable performance and it is unclear which provide the best results. We used the practical example of urban scenes to compare two of the top-performing algorithms. We found that when using the practical case of quantizing input and output imagery, the results were different than when using the conventional method … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 2 · 20 Jun 2017 · 7,849 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Constraint-Handling Technique for Genetic Algorithms using a Violation FactorAdam Chehouri, Rafic Younes, Jean Perron, Adrian IlincaOver the years, several meta-heuristic algorithms were proposed and are now emerging as common methods for constrained optimization problems. Among them, genetic algorithms (GA’s) shine as popular evolutionary algorithms (EA’s) in engineering optimization. Most engineering design problems are difficult to resolve with conventional optimization algorithms because they are highly nonlinear and contain constraints. In order to handle these constraints, the … …Journal of Computer Science, Vol. 12, Issue 7 · 31 Aug 2016 · 8,751 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleParameter Settings for New Generational Genetic Algorithms for Solving Global Optimization ProblemsSiew Mooi Lim, Md. Nasir Sulaiman, Norwati Mustapha, Abu Bakar Md. SultanThis study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent. …Journal of Computer Science, Vol. 11, Issue 11 · 7 Jan 2016 · 6,404 accessesView PDFCite