Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/6982
Title: Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
Authors: Puteh, Saad
Nor Khairah, Jamaludin
Nursalasawati, Rusli
Aryati, Bakri
Siti Sakira, Kamarudin
Keywords: Back-Propagation algorithm
Quick Propagation
Rice yield prediction
Conjugate gradient descent
Algorithms
Backpropagation network
Back propagation
Issue Date: 2004
Publisher: Universiti Malaysia Perlis
Abstract: Back Propagation algorithm(BP) has been popularly used to solve various problems, however it is shrouded with the problems of low convergence and instability. In recent years, improvements have been attempted to overcome the discrepancies aforementioned. In this study, we examine the performance of four enhanced BP algorithms to predict rice yield in MAD A plantation area in Kedah, Malaysia. A midst the four algorithms explored, Conjugate Gradient Descent exhibits the best performance.
URI: http://dspace.unimap.edu.my/123456789/6982
Appears in Collections:Universiti Malaysia Perlis



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