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167 results for “Optimization Algorithms”

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Research ArticleOpen accessPhrase in the titleMaximally Distant Codes Allocation Using Chemical Reaction Optimization and Ant Colony Optimization AlgorithmsTaisir Eldos, Waleed Nazih, Aws KananError correcting codes, also known as error controlling codes, are set of codes with redundancy that allows detecting errors. This is quite useful in transmitting data over a noisy channel or when retrieving data from a storage with possible physical defects. The idea is to use a set of code words that are maximally distant from each other, hence reducing … …Journal of Computer Science, Vol. 11, Issue 8 · 5 Nov 2015 · 7,004 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 · 8,096 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,180 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCargo Route Optimization Using Shortest Path Algorithms: Runtime and Validity ComparisonDedy Rahman Wijaya, Aqil Athallah, Tiara Nuha Noor’afina et al.The Indonesian logistics industry is facing significant challenges related to inefficiency and irregularity, particularly in the commodity cargo route system. This issue is further exacerbated by the high logistics costs in the country, which currently stands at 23%, higher than that of other countries. To address this issue, this study proposes an implementation and examination of several algorithms Greedy, Best … …Journal of Computer Science, Vol. 19, Issue 11 · 19 Oct 2023 · 6,355 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA SURVEY: PARTICLE SWARM OPTIMIZATION BASED ALGORITHMS TO SOLVE PREMATURE CONVERGENCE PROBLEMBahareh Nakisa, Mohd Zakree Ahmad Nazri, Mohammad Naim Rastgoo, Salwani AbdullahParticle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality … …Journal of Computer Science, Vol. 10, Issue 9 · 24 Apr 2014 · 8,788 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA SURVEY: PARTICLE SWARM OPTIMIZATION-BASED ALGORITHMS FOR GRID COMPUTING SCHEDULING SYSTEMSFaruku Umar Ambursa, Rohaya LatipBio-inspired heuristics have been promising in solving complex scheduling optimization problems. Several researches have been conducted to tackle the problems of task scheduling for the heterogeneous and dynamic grid systems using different bio-inspired mechanisms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO). PSO has been proven to have a relatively more promissing performance in dealing … …Journal of Computer Science, Vol. 9, Issue 12 · 25 Nov 2013 · 6,662 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTwo-Versions of Conjugate Gradient-Algorithms Based on Conjugacy Conditions for Unconstrained OptimizationAbbas Y. AL-Bayati, A.J. Salim, Khalel K. AbboProblem statement: (CG) algorithms, which we had investigated in this study, were widely used in optimization, especially for large scale optimization problems, because it did not need the storage of any matrix. The purpose of this construction was to find new CG-algorithms suitable for solving large scale optimization problems. Approach: Based on pure conjugacy condition and quadratic convex function two … …American Journal of Economics and Business Administration, Vol. 1, Issue 2 · 30 Jun 2009 · 8,113 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance Optimization of Discrete Wavelets Transform Based Image Watermarking Using Genetic AlgorithmsA. Al-Haj, A. Abu-ErrubThe excellent spatial localization, frequency spread and multi-resolution characteristics of the Discrete Wavelets Transform (DWT), which were similar to the theoretical models of the human visual system, facilitated the development of many imperceptible and robust DWT-based watermarking algorithms. There had been extremely few proposed algorithms on optimized DWT-based image watermarking that can simultaneously provide perceptual transparency and robustness since these … …Journal of Computer Science, Vol. 4, Issue 10 · 31 Oct 2008 · 6,326 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 · 6,410 accessesView PDFCite