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Data Analysis using Particle Swarm Optimization Algorithm
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Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization
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Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization
Published 2015“…Black Hole Algorithm (BH) is one of the optimization technique recently proposed for data clustering problem. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…However, MOPSO algorithm produces a group of non-dominated solutions which make the selection of an “appropriate” Pareto optimal or non-dominated solution more difficult. …”
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A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method
Published 2018“…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…Then, it proposes a type of swarm intelligence called Particle Swarm Optimization (PSO) algorithm to diminish cost though meeting deadlines. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values
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Research Reports -
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Kinetic Parameter Estimation in Alkylation of Benzene with 1-Decene through Hybrid Particle Swarm Optimization
Published 2012“…Afterwards, the solution obtained using PSO algorithm is given as initial guesses to the Levenberg–Marquardt algorithm to determine the improved optimal solution. …”
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Final Year Project -
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Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024“…The research strategically applies advanced algorithms to elevate PV-battery system performance and compares outcomes with Particle Swarm Optimization (PSO) and other studies, offering a comprehensive benchmark for evaluation…”
Conference Paper -
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Over the last decade (2014–2024), numerous approaches have been explored, each with its own optimization strengths and constraints. Swarm intelligence and evolutionary algorithms—including genetic algorithms, particle swarm optimization, and the zebra optimization algorithm—have operated effectively in this area. …”
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An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization
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Book Chapter -
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A guided particle swarm optimization algorithm for nurse scheduling problem
Published 2014“…Basari, “An Investigation of. The proposed algorithms are tested on the real data and the obtained results demonstrate that the proposed particle swarm optimization has better performance to cope with complex scheduling problem. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024thesis::doctoral thesis -
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Thesis -
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. Updated KDD CUP data set is formed and used during the training and testing phases, where this data set consists of mixed data traffics between attacks and normal activities. …”
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