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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/6424

Title: Backpropagation algorithm for rice yield prediction
Authors: Puteh, Saad
Mohamed Rizon, Mohamed Juhari
Nor Khairah, Jamaludin
Siti Sakira, Kamarudin
Aryati, Bakri
Nursalasawati, Rusli
Keywords: BP;Rice yield prediction;Improved unit range;Rice yield;Neural networks (Computer science);Back propagation;Algorithms;Computer programming
Issue Date: 28-Jan-2004
Publisher: Oita University
Citation: p.148-151
Series/Report no.: Proceedings of the 9th International Symposium on Artificial Life and Robotics (AROB 9th '04)
Abstract: Parameters that affect rice yield are many, for instance diseases, pests and weeds. Statistical or mathematical model is unable to describe the correlation between plant diseases, pests and weeds on the amount of rice yield. In this study, a Backpropogation (BP) algorithm is utilized to develop a neural network model to predict rice yield based on the aforementioned factors in MUDA irrigation area, Malaysia. The result of this study shows that the BP algorithm is able to predict the rice yield to a deviation of less than 0.21.
Description: Organized by Oita University, 28th - 30th January 2004 at Beppu, Oita, Japan.
URI: http://hdl.handle.net/123456789/6424
Appears in Collections:Conference Papers
Mohd. Rizon Mohamed Juhari, Prof. Ir. Dr.

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