1. DSpaceCRIS@UNITEN
  2. College of Engineering
  3. COE Scholarly Publication
Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/9486
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dc.contributor.authorVasuntha, K.
dc.contributor.authorMalek, M.A.
dc.contributor.authorMustapha, A.
dc.contributor.authorIdris, H.
dc.date.accessioned2018-03-01T03:43:58Z-
dc.date.available2018-03-01T03:43:58Z-
dc.date.issued2014
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/9486-
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.
dc.titleYield prediction for rubber“Hevea Brasiliensis” in Malaysia: A review
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:COE Scholarly Publication
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