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Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction

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dc.citedby1
dc.contributor.authorMarlan Z.M.en_US
dc.contributor.authorRamlie F.en_US
dc.contributor.authorJamaludin K.R.en_US
dc.contributor.authorHarudin N.en_US
dc.contributor.authorid57223885180en_US
dc.contributor.authorid55982859700en_US
dc.contributor.authorid26434395500en_US
dc.contributor.authorid56319654100en_US
dc.date.accessioned2023-05-29T09:36:26Z
dc.date.available2023-05-29T09:36:26Z
dc.date.issued2022
dc.description.abstractAnalysis of multivariate historical information in predicting future state or unknown outcomes is the core function of Taguchi�s T-method. Introduced by Dr. Genichi Taguchi under Mahalanobis-Taguchi system, the T-method combines regression principle and robust quality engineering element in formulating a predictive model and employs taguchi�s orthogonal array design in optimizing the model through feature or variable selection process. There is a concern regarding the sub-optimality of the T-method prediction accuracy, particularly when the orthogonal array failed to offer a significant number of combinations in search for an optimal subset of features. This is due to the fixed and limited combination offered for evaluation as well as the lack of higher-order interaction of combination. In response to this issue, this paper proposed an angle modulated Bat algorithm to be integrated with the T-method in optimizing the prediction model. A comparison study was conducted using energy efficiency benchmark datasets with the mean absolute error metric used as the performance measure. The results show that the proposed method improved the prediction accuracy by 10.74%, from 6.05 to 5.4, by integrating only four features over the original eight in the prediction model. � 2022, Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/eei.v11i5.4350
dc.identifier.epage2835
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85136022775
dc.identifier.spage2828
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85136022775&doi=10.11591%2feei.v11i5.4350&partnerID=40&md5=bdc5eae3e902c1a1ebe4cc1617ffae72
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26738
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.titleEnhanced Taguchi�s T-method using angle modulated Bat algorithm for predictionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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