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: Article
Language:English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2009
Subjects:
Online Access:http://ir.unimas.my/id/eprint/3106/
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
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author Lim, D.K.H
Kolay, P.K
author_facet Lim, D.K.H
Kolay, P.K
author_sort Lim, D.K.H
building UNIMAS Institutional Repository
collection Online Access
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.
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format Article
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institution Universiti Malaysia Sarawak
institution_category Local University
language English
last_indexed 2025-11-15T06:03:10Z
publishDate 2009
publisher Universiti Malaysia Sarawak, (UNIMAS)
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spelling unimas-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 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).
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)
title 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_short 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)
topic TC Hydraulic engineering. Ocean engineering
url http://ir.unimas.my/id/eprint/3106/
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