1. DSpaceCRIS@UNITEN
  2. Institute of Energy Policy and Research (IEPRE)
  3. IPRE Scholarly Publication
Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/9483
DC FieldValueLanguage
dc.contributor.authorKhidzir, A.B.M.en_US
dc.contributor.authorMalek, M.A.en_US
dc.contributor.authorIsmail, A.R.en_US
dc.contributor.authorJuneng, L.en_US
dc.contributor.authorChun, T.S.en_US
dc.date.accessioned2018-03-01T03:43:57Z-
dc.date.available2018-03-01T03:43:57Z-
dc.date.issued2015-
dc.description.abstractThis paper proposed an Artificial Immune System (AIS) approach using the Clonal Selection Based Algorithms (CSA) to analyze the pattern recognition capability of the paddy trend, and to predict the paddy production based on climate change effects. Climate factors and paddy production are used as input parameters. High percentage of accuracy ranges from 90%-92% is obtained throughout the training, validation and testing steps of the model. The results of the study were tested using the Root Mean Square Error (RMSE), Mean Average Percentage Error (MAPE) and coefficient of determination (R2). Based on the results of this study, it can be concluded that the CSA is a reliable tool to be used as pattern recognition and prediction of paddy production. © 2006-2015 Asian Research Publishing Network (ARPN).-
dc.language.isoenen_US
dc.titleUtilization of artificial immune system in prediction of paddy productionen_US
dc.typeArticleen_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:IPRE Scholarly Publication
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.