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Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)

Hydraulic conductivity of tropical soils is very complex. Several hydraulic conductivity prediction methods have focuses on laboratory and field tests, such as Constant Head Test, Falling Head Test, Ring Infiltrometer, Instantaneous profile method and Test basin. This study demonstrate the compariso...

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Main Authors: Lim, D.K.H, Kolay, P.K
Format: E-Article
Language:English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2009
Subjects:
TC Hydraulic engineering. Ocean engineering
Online Access:http://ir.unimas.my/id/eprint/3106/1/Predicting%20Hydraulic%20conductivity%20%28k%29%20of%20tropical%20soils%20by%20using%20artificial%20neural%20network%20%28ANN%29.pdf
http://ir.unimas.my/id/eprint/3106/
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spelling my.unimas.ir.31062015-03-23T03:32:42Z http://ir.unimas.my/id/eprint/3106/ Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN) Lim, D.K.H Kolay, P.K TC Hydraulic engineering. Ocean engineering Hydraulic conductivity of tropical soils is very complex. Several hydraulic conductivity prediction methods have focuses on laboratory and field tests, such as Constant Head Test, Falling Head Test, Ring Infiltrometer, Instantaneous profile method and Test basin. This study demonstrate the comparison between the conventional estimation of k by using Shepard's equation for approximating k and the predicted k from ANN. Universiti Malaysia Sarawak, (UNIMAS) 2009 E-Article NonPeerReviewed text en http://ir.unimas.my/id/eprint/3106/1/Predicting%20Hydraulic%20conductivity%20%28k%29%20of%20tropical%20soils%20by%20using%20artificial%20neural%20network%20%28ANN%29.pdf Lim, D.K.H and Kolay, P.K (2009) Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN). UNIMAS E-Journal of civil Engineering, 1 (1).
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TC Hydraulic engineering. Ocean engineering
spellingShingle TC Hydraulic engineering. Ocean engineering
Lim, D.K.H
Kolay, P.K
Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
description Hydraulic conductivity of tropical soils is very complex. Several hydraulic conductivity prediction methods have focuses on laboratory and field tests, such as Constant Head Test, Falling Head Test, Ring Infiltrometer, Instantaneous profile method and Test basin. This study demonstrate the comparison between the conventional estimation of k by using Shepard's equation for approximating k and the predicted k from ANN.
format E-Article
author Lim, D.K.H
Kolay, P.K
author_facet Lim, D.K.H
Kolay, P.K
author_sort Lim, D.K.H
title Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
title_short Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
title_full Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
title_fullStr Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
title_full_unstemmed Predicting Hydraulic conductivity (k) of tropical soils by using artificial neural network (ANN)
title_sort predicting hydraulic conductivity (k) of tropical soils by using artificial neural network (ann)
publisher Universiti Malaysia Sarawak, (UNIMAS)
publishDate 2009
url http://ir.unimas.my/id/eprint/3106/1/Predicting%20Hydraulic%20conductivity%20%28k%29%20of%20tropical%20soils%20by%20using%20artificial%20neural%20network%20%28ANN%29.pdf
http://ir.unimas.my/id/eprint/3106/
_version_ 1644509261911293952
score 13.154949

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