Publication:
Yield prediction for rubber“Hevea Brasiliensis” in Malaysia: A review

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dc.contributor.authorVasuntha K.en_US
dc.contributor.authorMalek M.A.en_US
dc.contributor.authorMustapha A.en_US
dc.contributor.authorIdris H.en_US
dc.contributor.authorid56461404100en_US
dc.contributor.authorid55636320055en_US
dc.contributor.authorid57200530694en_US
dc.contributor.authorid55991687900en_US
dc.date.accessioned2023-05-16T02:46:40Z
dc.date.available2023-05-16T02:46:40Z
dc.date.issued2014
dc.description.abstractThis study focuses on the efforts to promote the productivity of rubber yield under unpredictable climate behavior currently experience in Malaysia. Artificial Neural Network (ANN) is the method chosen in predicting natural rubber production in relation to climate variables over the past years. One of the explicit criteria of ANN is the ability of the network to deal with non linear data and its capability of learning from historical data. © Research India Publications.en_US
dc.description.natureFinalen_US
dc.identifier.epage23144
dc.identifier.issue23
dc.identifier.scopus2-s2.0-84919784635
dc.identifier.spage23133
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84919784635&partnerID=40&md5=ba95ede5cc1d2a774bffc639cd72ef7e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22014
dc.identifier.volume9
dc.publisherResearch India Publicationsen_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Applied Engineering Research
dc.titleYield prediction for rubber“Hevea Brasiliensis” in Malaysia: A reviewen_US
dc.typeReviewen_US
dspace.entity.typePublication
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