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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction

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dc.citedby2
dc.contributor.authorMarlan Z.M.en_US
dc.contributor.authorJamaludin K.R.en_US
dc.contributor.authorRamlie F.en_US
dc.contributor.authorHarudin N.en_US
dc.contributor.authorid57223885180en_US
dc.contributor.authorid26434395500en_US
dc.contributor.authorid55982859700en_US
dc.contributor.authorid56319654100en_US
dc.date.accessioned2023-05-29T09:36:54Z
dc.date.available2023-05-29T09:36:54Z
dc.date.issued2022
dc.description.abstractTaguchi�s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi�s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. A comparative study is conducted by comparing the performance of the proposed method against the conventional approach using mean absolute error as the performance measure on four benchmark case studies. The results from experimental studies show a significant improvement in the T-method prediction accuracy. A reduction in the total number of features results in a less complex model. Based on the general observation, the nearest integer-based binary bat algorithm successfully optimized the selection of significant features due to recursive and repetitive searchability, in addition to its adaptive element in response to the current best solution in guiding the search process towards optimality. � 2022, Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/eei.v11i4.3859
dc.identifier.epage2224
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85133471399
dc.identifier.spage2215
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85133471399&doi=10.11591%2feei.v11i4.3859&partnerID=40&md5=0a45c560d6b4f581e6de275be50753f2
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26812
dc.identifier.volume11
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleBulletin of Electrical Engineering and Informatics
dc.titleTaguchi's T-method with nearest integer-based binary bat algorithm for predictionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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