Universiti Teknologi Malaysia Institutional Repository

Rice yield classification using backpropagation network

Saad, Puteh and Jamaludin, Nor Khairah and Kamarudin, Siti Sakira and Bakri, Aryati and Rusli, Nursalasawati (2004) Rice yield classification using backpropagation network. Journal of Information and Communication Technology (JICT), 3 (1). pp. 67-81. ISSN 2180-3862

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Official URL: http://www.jict.uum.edu.my/index.php/previous-issu...


Among factors that affect rice yield are diseases, pests and weeds. It is intractable to model the correlation between plant diseases, pests and weeds on the amount of rice yield statistically and mathematically. In this study, a backpropagation network (BPN) is developed to classify rice yield based on the aforementioned factors in MUDA irrigation area Malaysia. The result of this study shows that BPN is able to classify the rice yield to a deviation of 0.03.

Item Type:Article
Uncontrolled Keywords:backpropagation network, classification, rice yield, pests, diseases, and weeds
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:28180
Deposited By: Yanti Mohd Shah
Deposited On:18 Sep 2012 06:16
Last Modified:30 Nov 2018 07:07

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