An ensemble evolutionary approach in evaluation of surface finish reduction of vibratory finishing process

dc.contributor.authorSangwan, Kuldip Singh
dc.date.accessioned2023-08-31T07:15:49Z
dc.date.available2023-08-31T07:15:49Z
dc.date.issued2015-07
dc.description.abstractThe functioning of multi-gene genetic programming (MGGP) algorithm suffers from the problem of difficulty in model selection. During the preliminary analysis, it is observed that there are many models in the population whose performance is better than that of the model selected with a little compromise on training error. Therefore, an ensemble evolutionary (Ensemble-MGGP) approach is proposed and applied to the data obtained from the vibratory finishing process. The paper aims to discuss these issues.en_US
dc.identifier.urihttps://www.emerald.com/insight/content/doi/10.1108/EC-03-2014-0047/full/html
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11756
dc.language.isoenen_US
dc.publisherEmeralden_US
dc.subjectMechanical Engineeringen_US
dc.subjectSurface finish predictionen_US
dc.subjectVibratory finishing process modellingen_US
dc.subjectVibratory modellingen_US
dc.titleAn ensemble evolutionary approach in evaluation of surface finish reduction of vibratory finishing processen_US
dc.typeArticleen_US

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