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dc.contributor.authorMafarja, Majdi M
dc.contributor.authorMirjalili, Seyedali
dc.date.accessioned2017-12-11T02:16:09Z
dc.date.available2017-12-11T02:16:09Z
dc.date.issued2017
dc.identifier.issn0925-2312
dc.identifier.doi10.1016/j.neucom.2017.04.053
dc.identifier.urihttp://hdl.handle.net/10072/355239
dc.description.abstractHybrid metaheuristics are of the most interesting recent trends in optimization and memetic algorithms. In this paper, two hybridization models are used to design different feature selection techniques based on Whale Optimization Algorithm (WOA). In the first model, Simulated Annealing (SA) algorithm is embedded in WOA algorithm, while it is used to improve the best solution found after each iteration of WOA algorithm in the second model. The goal of using SA here is to enhance the exploitation by searching the most promising regions located by WOA algorithm. The performance of the proposed approaches is evaluated on 18 standard benchmark datasets from UCI repository and compared with three well-known wrapper feature selection methods in the literature. The experimental results confirm the efficiency of the proposed approaches in improving the classification accuracy compared to other wrapper-based algorithms, which insures the ability of WOA algorithm in searching the feature space and selecting the most informative attributes for classification tasks.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherElsevier
dc.relation.ispartofpagefrom302
dc.relation.ispartofpageto312
dc.relation.ispartofjournalNeurocomputing
dc.relation.ispartofvolume260
dc.subject.fieldofresearchInformation and Computing Sciences not elsewhere classified
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchPsychology and Cognitive Sciences
dc.subject.fieldofresearchcode089999
dc.subject.fieldofresearchcode08
dc.subject.fieldofresearchcode09
dc.subject.fieldofresearchcode17
dc.titleHybrid Whale Optimization Algorithm with simulated annealing for feature selection
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorMirjalili, Seyedali


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