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7 articles for “Premature Convergence”

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Research ArticleOpen accessPhrase 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 · 8,783 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCombined Heuristic Technique for Optimization of Bloom Filter in Spam FilteringArulanand Natarajan, S. Subramanian, K. PremalathaProblem statement: Spam is an irrelevant or inappropriate message sent on the internet to a large number of newsgroups or users. A spam word is a list of well-known words that often appear in spam mails. Bloom Filter (BF) is used for identification of spam word. Approach: BF is a simple but powerful data structure that can check membership to … …Journal of Computer Science, Vol. 7, Issue 9 · 27 Jul 2011 · 7,226 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Weighting Technique Based Arctic Puffin Optimization for Energy Efficient Data Transmission in Wireless Sensor NetworksM. Bharathraj Kumar, S. Avinash, Prakash G. Gani, Prathapchandra ShettyWireless Sensor Networks (WSNs) are designed using various sensor nodes, which are employed for communication in diverse applications that include healthcare, industrial areas, and smart cities. Specifically, WSNs demand energy-efficient clustering and routing mechanisms that assist in extending network lifetime due to the limited battery capacity of sensor nodes. However, many existing meta-heuristic-based approaches incorporate fixed objective weights that struggle … …Journal of Computer Science, Vol. 22, Issue 9 · 10 Sep 2026 · 767 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Cloud Load Balancing Using Deep Q-Learning With Inverted S-Shaped Hierarchical Reverse Superb Fairy-Wren OptimizationB. R. Yogeetha, S. P. AnandarajCloud computing offers a scalable and cost-effective platform by providing on-demand access to shared computational resources. However, effective load balancing is essential to maintain optimal performance and maximize resource utilization for ensuring even distribution of network traffic across servers, preventing overload, improving response time and enhancing the system reliability. This manuscript proposes the Deep Q-Network with Inverted S-shaped Hierarchical Reverse … …Journal of Computer Science, Vol. 22, Issue 6 · 4 Jun 2026 · 1,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Meta-Heuristic for Multi-Objective Integrated Procurement, Production and Distribution Problem of Supply Chain Network Under Fuzziness UncertaintiesKaoutar Douaioui, Mouhsene Fri, Charif Mabrouki, El Alami SemmaIn this study, we devoted a design under uncertainty of a supply chain network composed of multiple suppliers, multiple plants, multiple distributors and multiple customers. The proposed model is a bi- objective mixed integer linear programming which consider several constraints and optimize the total costs including the procurement, production, storage and distribution costs as well as maximize on-time deliveries. In … …Journal of Computer Science, Vol. 17, Issue 12 · 27 Dec 2021 · 6,625 accessesView PDFCite
Research ArticleOpen accessIn the abstractPROBABILISTIC PERIODIC REVIEW INVENTORYMODELUSING LAGRANGE TECHNIQUE AND FUZZY ADAPTIVE PARTICLE SWARM OPTIMIZATIONH. A. Fergany, N. A. El-Hefnawy, O. M. HollahThe integration between inventory model and Artificial Intelligent (AI) represents the rich area of research since last decade. In this study we investigate probabilistic periodic review <Q<qm, N> inventory model with mixture shortage (backorder and lost sales) using Lagrange multiplier technique and Fuzzy Adaptive Particle Swarm Optimization (FAPSO) under restrictions. The objective of these algorithms is to find the optimal … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 11 Aug 2014 · 7,017 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybridization of Enhanced Artificial Bee Colony-Least Squares Support Vector Machines for Price ForecastingZuriani Mustaffa, Yuhanis YusofProblem statement: As the performance of Least Squares Support Vector Machines (LSSVM) is highly rely on its value of regularization parameter, γ and kernel parameter, σ2, man-made approach is clearly not an appropriate solution since it may lead to blindness in certain extent. In addition, this technique is time consuming and unsystematic, which consequently affect the generalization performance of LSSVM. … …Journal of Computer Science, Vol. 8, Issue 10 · 28 Aug 2012 · 6,796 accessesView PDFCite