Utilization of artificial immune system in prediction of paddy production

A. B M Khidzir, Marlinda Abdul Malek, Amelia Ritahani Ismail, Liew Juneng, Ting Sie Chun

Research output: Contribution to journalArticle

Abstract

This 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.

Original languageEnglish
Pages (from-to)1462-1467
Number of pages6
JournalARPN Journal of Engineering and Applied Sciences
Volume10
Issue number3
Publication statusPublished - 2015

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Immune system
Pattern recognition
Climate change
Mean square error
Testing

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Khidzir, A. B M ; Abdul Malek, Marlinda ; Ismail, Amelia Ritahani ; Juneng, Liew ; Chun, Ting Sie. / Utilization of artificial immune system in prediction of paddy production. In: ARPN Journal of Engineering and Applied Sciences. 2015 ; Vol. 10, No. 3. pp. 1462-1467.
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Utilization of artificial immune system in prediction of paddy production. / Khidzir, A. B M; Abdul Malek, Marlinda; Ismail, Amelia Ritahani; Juneng, Liew; Chun, Ting Sie.

In: ARPN Journal of Engineering and Applied Sciences, Vol. 10, No. 3, 2015, p. 1462-1467.

Research output: Contribution to journalArticle

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