Search Results - (( optimal solution clustering algorithm ) OR ( java application modified algorithm ))
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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 novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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A review: accuracy optimization in clustering ensembles using genetic algorithms
Published 2011“…It combines multiple partitions generated by different clustering algorithms into a single clustering solution. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Balancing exploration and exploitation in ACS algorithms for data clustering
Published 2019“…This makes the algorithm deviate from the clustering solution and performs a biased exploration. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…However, the PSO algorithm produces a group of non-dominated solutions which makes the choice of a “suitable” Pareto optimal or non-dominated solution more difficult. …”
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8
An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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Performance analysis of clustering based genetic algorithm
Published 2016“…Population Control and Polygamy mating techniques were introduced to improve the performance of the algorithm. Results obtained from the determination of optimal solutions to the : Sphere; Schwefel 2.4; Beale and another known optimization functions carried out in this work shows that the proposed CGA converges to global solutions within few iterations and can also be adopted for function optimization aside from the route optimization problem previously reported in Literature.…”
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Proceeding Paper -
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Basic firefly algorithm for document clustering
Published 2015“…The Document clustering plays significant role in Information Retrieval (IR) where it organizes documents prior to the retrieval process.To date, various clustering algorithms have been proposed and this includes the K-means and Particle Swarm Optimization. …”
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Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization
Published 2022“…Considering multi-metric approaches and their implicit conflicting nature, it is necessary to handle this through effective multi-objective optimization algorithms. An effective optimization can be handled using a meta-heuristic approach with a high level of solution interactions. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
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Ringed seal search for global optimization via a sensitive search model / Younes Saadi
Published 2018“…Finally, the proposed algorithm is applied on a data clustering case study using seven benchmark datasets to validate and check its ability to solve real optimization problems. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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