Rice yield prediction - a comparison between enhanced 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: Saad, Puteh, Jamaludin, Nor Khairah, Rusli, Nursalasawati, Bakri, Aryati, Kamarudin, Siti Sakira
Format: Article
Language:en
Published: Penerbit UTM Press 2004
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Online Access:http://eprints.utm.my/3410/1/aryati_-_Rice_Yield_Prediction_-_A_Comparison_between_Enhanced_Back_Propagation_Learning.pdf
http://eprints.utm.my/3410/
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author Saad, Puteh
Jamaludin, Nor Khairah
Rusli, Nursalasawati
Bakri, Aryati
Kamarudin, Siti Sakira
author_facet Saad, Puteh
Jamaludin, Nor Khairah
Rusli, Nursalasawati
Bakri, Aryati
Kamarudin, Siti Sakira
author_sort Saad, Puteh
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
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 MADA plantation area in Kedah, Malaysia. Amidst the four algorithms explored, Conjugate Gradient Descent exhibits the best performance.
format Article
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institution Universiti Teknologi Malaysia
language en
publishDate 2004
publisher Penerbit UTM Press
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spelling my.utm.eprints-34102017-11-01T04:17:37Z http://eprints.utm.my/3410/ Rice yield prediction - a comparison between enhanced back propagation learning algorithms Saad, Puteh Jamaludin, Nor Khairah Rusli, Nursalasawati Bakri, Aryati Kamarudin, Siti Sakira QA75 Electronic computers. Computer science 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 MADA plantation area in Kedah, Malaysia. Amidst the four algorithms explored, Conjugate Gradient Descent exhibits the best performance. Penerbit UTM Press 2004-06 Article PeerReviewed application/pdf en http://eprints.utm.my/3410/1/aryati_-_Rice_Yield_Prediction_-_A_Comparison_between_Enhanced_Back_Propagation_Learning.pdf Saad, Puteh and Jamaludin, Nor Khairah and Rusli, Nursalasawati and Bakri, Aryati and Kamarudin, Siti Sakira (2004) Rice yield prediction - a comparison between enhanced back propagation learning algorithms. Jurnal Teknologi Maklumat, 16 (1). pp. 27-34. ISSN 0128-3790
spellingShingle QA75 Electronic computers. Computer science
Saad, Puteh
Jamaludin, Nor Khairah
Rusli, Nursalasawati
Bakri, Aryati
Kamarudin, Siti Sakira
Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title_full Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title_fullStr Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title_full_unstemmed Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title_short Rice yield prediction - a comparison between enhanced back propagation learning algorithms
title_sort rice yield prediction - a comparison between enhanced back propagation learning algorithms
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/3410/1/aryati_-_Rice_Yield_Prediction_-_A_Comparison_between_Enhanced_Back_Propagation_Learning.pdf
http://eprints.utm.my/3410/
url_provider http://eprints.utm.my/