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River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia

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Format: Citation Index Journal
Published: 2012
Online Access:http://eprints.utp.edu.my/9512/
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id my.utp.eprints.9512
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spelling my.utp.eprints.95122013-04-02T05:24:53Z River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia 2012 Citation Index Journal NonPeerReviewed UNSPECIFIED (2012) River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia. [Citation Index Journal] http://eprints.utp.edu.my/9512/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
format Citation Index Journal
title River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
spellingShingle River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
title_short River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
title_full River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
title_fullStr River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
title_full_unstemmed River suspended sediment prediction using various multilayer perceptron neural network training algorithms-A case study in Malaysia
title_sort river suspended sediment prediction using various multilayer perceptron neural network training algorithms-a case study in malaysia
publishDate 2012
url http://eprints.utp.edu.my/9512/
_version_ 1738655755798577152
score 13.188404

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