A Novel Multimean Particle Swarm Optimization Algorithm for Nonlinear Continuous Optimization: Application to Feed-Forward Neural Network Training

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dc.contributor.authorHacibeyoglu, Mehmet
dc.contributor.authorIbrahim, Mohammed H.
dc.date.accessioned2024-02-23T14:26:32Z
dc.date.available2024-02-23T14:26:32Z
dc.date.issued2018
dc.departmentNEÜen_US
dc.description.abstractMultilayer feed-forward artificial neural networks are one of the most frequently used data mining methods for classification, recognition, and prediction problems. The classification accuracy of a multilayer feed-forward artificial neural networks is proportional to training. A well-trained multilayer feed-forward artificial neural networks can predict the class value of an unseen sample correctly if provided with the optimum weights. Determining the optimum weights is a nonlinear continuous optimization problem that can be solved with metaheuristic algorithms. In this paper, we propose a novelmultimean particle swarmoptimization algorithm for multilayer feed-forward artificial neural networks training. The proposed multimean particle swarm optimization algorithm searches the solution space more efficiently with multiple swarms and finds better solutions than particle swarm optimization. To evaluate the performance of the proposed multimean particle swarm optimization algorithm, experiments are conducted on ten benchmark datasets from the UCI repository and the obtained results are compared to the results of particle swarm optimization and other previous research in the literature. The analysis of the results demonstrated that the proposed multimean particle swarm optimization algorithm performed well and it can be adopted as a novel algorithm for multilayer feedforward artificial neural networks training.en_US
dc.description.sponsorshipBAP Coordination Office of Necmettin Erbakan Universityen_US
dc.description.sponsorshipThis paper is supported by BAP Coordination Office of Necmettin Erbakan University.en_US
dc.identifier.doi10.1155/2018/1435810
dc.identifier.issn1058-9244
dc.identifier.issn1875-919X
dc.identifier.scopus2-s2.0-85050177157en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1155/2018/1435810
dc.identifier.urihttps://hdl.handle.net/20.500.12452/14236
dc.identifier.volume2018en_US
dc.identifier.wosWOS:000438856700001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherHindawi Ltden_US
dc.relation.ispartofScientific Programmingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject[Keyword Not Available]en_US
dc.titleA Novel Multimean Particle Swarm Optimization Algorithm for Nonlinear Continuous Optimization: Application to Feed-Forward Neural Network Trainingen_US
dc.typeArticleen_US

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