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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 13.15806

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