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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The HFPSO technique hybridizes the Firefly Optimization (FFO) algorithm and the Particle Swarm Optimization (PSO) method to improve the exploitation and exploration strategies and enhance the convergence rate. …”
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Optimizing optimal path trace back system for Smith-Waterman algorithm using structural modelling technique: article
Published 2012“…back system for Smith-Waterman Algorithm using Structural Modelling Technique. The objectives for this paper are to optimize the best trace back scanning performance and also to design the simple architecture in order to reduce the runtime. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Hence, optimization algorithms, consisting of exact and heuristic methods, are crucial for a myriad of real-world applications. …”
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A Biogeography-Based Optimization Algorithm Hybridized With Tabu Search For The Quadratic Assignment Problem
Published 2016“…Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. …”
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A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem
Published 2016“…The quadratic assignment problem (QAP) is an NP hard combinatorial optimization problem with a wide variety of applications.Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems.It has been shown that BBO provides performance on a par with other optimization methods.A classical BBO algorithm employs the mutation operator as its diversification strategy. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…The obtained results of the proposed algorithm are compared to simulated results of the original Particle Swarm Optimization (PSO) method and the present state-of-the-art optimization techniques. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. …”
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Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm
Published 2020“…Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. …”
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Among multi-objective evolutionary algorithms proposed in the literature, particle swarm optimization (PSO)-based multi-objective (MOPSO) algorithm has been cited to be the most representative. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…In an attempt to address this problem, the clustering-based method that utilizes crowding distance (CD) technique to balance the optimality of the objectives in Pareto optimal solution search is proposed. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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