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A survey on improvement of Mahalanobis Taguchi system and its application

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dc.citedby3
dc.contributor.authorTan L.M.en_US
dc.contributor.authorWan Muhamad W.Z.A.en_US
dc.contributor.authorYahya Z.R.en_US
dc.contributor.authorJunoh A.K.en_US
dc.contributor.authorAzziz N.H.A.en_US
dc.contributor.authorRamlie F.en_US
dc.contributor.authorHarudin N.en_US
dc.contributor.authorAbu M.Y.en_US
dc.contributor.authorTan X.J.en_US
dc.contributor.authorid58193432800en_US
dc.contributor.authorid55860800560en_US
dc.contributor.authorid50862369800en_US
dc.contributor.authorid38561331300en_US
dc.contributor.authorid57190941028en_US
dc.contributor.authorid55982859700en_US
dc.contributor.authorid56319654100en_US
dc.contributor.authorid55983627200en_US
dc.contributor.authorid57779474600en_US
dc.date.accessioned2024-10-14T03:17:35Z
dc.date.available2024-10-14T03:17:35Z
dc.date.issued2023
dc.description.abstractMahalanobis Taguchi System (MTS) is used for pattern recognition and classification, diagnosis, and prediction of a multivariate data set. Mahalanobis Distance (MD), orthogonal array (OA), and signal-to-noise ratio (SNR) are used in traditional MTS in order to identify and optimize the variables. However, the high correlation among variables shows an effect on the inverse of the correlation matrix that uses in the calculation of MD and hence affects the accuracy of the MD. Therefore, Mahalanobis-Taguchi-Gram-Schmidt (MTGS) system is proposed in order to solve the problem of multicollinearity. The value of MD can be calculated by using the Gram-Schmidt Orthogonalization Process (GSOP). Besides, the computational speed and the accuracy in optimization using OA and SNR are other issues that are concerned the authors. Hence, the combination of MTS and other methods such as Binary Particles Swarm Optimization (BPSO) and Binary Ant Colony Optimization (NBACO) is proposed to improve the computational speed and the accuracy in optimization. The purpose of this paper is to review and summarize some works that developed and used the hybrid methodology of MTS as well as its application in several fields. Moreover, a discussion about the future work that can be done related to MTS is carried out. � 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/s11042-023-15257-5
dc.identifier.epage43881
dc.identifier.issue28
dc.identifier.scopus2-s2.0-85153384535
dc.identifier.spage43865
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85153384535&doi=10.1007%2fs11042-023-15257-5&partnerID=40&md5=fc0f4c2b9d254f8c0cbda04b8aba28e6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/33987
dc.identifier.volume82
dc.pagecount16
dc.publisherSpringeren_US
dc.sourceScopus
dc.sourcetitleMultimedia Tools and Applications
dc.subjectMahalanobis distance
dc.subjectMahalanobis Taguchi system
dc.subjectMahalanobis-Taguchi-Gram-Schdimt, Optimization
dc.subjectMetaheuristic algorithm
dc.subjectSignal-to-noise ratio, Orthogonal Array
dc.subjectAnt colony optimization
dc.subjectClassification (of information)
dc.subjectComputer aided diagnosis
dc.subjectInverse problems
dc.subjectPattern recognition
dc.subjectRegression analysis
dc.subjectITS applications
dc.subjectMahalanobi-taguchi-gram-schdimt, optimization
dc.subjectMahalanobis
dc.subjectMahalanobis distances
dc.subjectMahalanobis-taguchi systems
dc.subjectMeta-heuristics algorithms
dc.subjectOptimisations
dc.subjectOrthogonal array
dc.subjectSignal-to-noise ratio, orthogonal array
dc.subjectSystem applications
dc.subjectSignal to noise ratio
dc.titleA survey on improvement of Mahalanobis Taguchi system and its applicationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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