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Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms

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...

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Main Authors:	Puteh, Saad, Nor Khairah, Jamaludin, Nursalasawati, Rusli, Aryati, Bakri, Siti Sakira, Kamarudin
Format:	Article
Language:	English
Published:	Universiti Malaysia Perlis 2009
Subjects:	Back-Propagation algorithm Quick Propagation Rice yield prediction Conjugate gradient descent Algorithms Backpropagation network Back propagation
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/6982
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id	my.unimap-6982
record_format	dspace
spelling	my.unimap-69822009-08-18T05:03:06Z Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms Puteh, Saad Nor Khairah, Jamaludin Nursalasawati, Rusli Aryati, Bakri Siti Sakira, Kamarudin Back-Propagation algorithm Quick Propagation Rice yield prediction Conjugate gradient descent Algorithms Backpropagation network Back propagation 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. 2009-08-18T05:03:05Z 2009-08-18T05:03:05Z 2004 Article http://hdl.handle.net/123456789/6982 en Universiti Malaysia Perlis
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Back-Propagation algorithm Quick Propagation Rice yield prediction Conjugate gradient descent Algorithms Backpropagation network Back propagation
spellingShingle	Back-Propagation algorithm Quick Propagation Rice yield prediction Conjugate gradient descent Algorithms Backpropagation network Back propagation Puteh, Saad Nor Khairah, Jamaludin Nursalasawati, Rusli Aryati, Bakri Siti Sakira, Kamarudin Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
description	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.
format	Article
author	Puteh, Saad Nor Khairah, Jamaludin Nursalasawati, Rusli Aryati, Bakri Siti Sakira, Kamarudin
author_facet	Puteh, Saad Nor Khairah, Jamaludin Nursalasawati, Rusli Aryati, Bakri Siti Sakira, Kamarudin
author_sort	Puteh, Saad
title	Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
title_short	Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
title_full	Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
title_fullStr	Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
title_full_unstemmed	Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms
title_sort	rice yield prediction - a comparison between enchanced back propagation learning algorithms
publisher	Universiti Malaysia Perlis
publishDate	2009
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/6982
_version_	1643788583437336576
score	13.222552

Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms

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