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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach

From standard static formula for bearing capacity of a single pile foundation, an algorithm using a reliability approach for the determination of service load was developed. Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; ins...

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Main Authors: Ab. Malik, Rosely, Jamil S., Mohamed
Format: Article
Language:English
English
Published: Universiti Putra Malaysia Press 2001
Online Access:http://psasir.upm.edu.my/id/eprint/3678/1/The_Determination_of_Pile_Capacity_Using_Artificial_Neural-net.pdf
http://psasir.upm.edu.my/id/eprint/3678/
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spelling my.upm.eprints.36782013-05-27T07:10:22Z http://psasir.upm.edu.my/id/eprint/3678/ The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach Ab. Malik, Rosely Jamil S., Mohamed From standard static formula for bearing capacity of a single pile foundation, an algorithm using a reliability approach for the determination of service load was developed. Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. In this study, the developed algorithm is further expanded to include computation of the weight-matrix of a sequential associative feedback-type neural net model for the determination of service load of a single pile is introduced. The proposed technique concludes improved efficiency over the conventional method of commissioning the functional formula of the weights by exploiting the structural properties of the matrices appeared in the codification of the service load to a single pile problem as a quadratic zero-one optimization program. Those structural attributes are distinguished and described in terms of template-matrix contributions of the constraint functions of the quadratic optimization, to the weight-matrix asynchronous auto-associative neural net It is stated by using those templates, the weight matrix can be taken in intuitively. Performance results of this research study reveal that neural net deterministic approach could be a better choice for implementation in identifying the required weight-matrix. Universiti Putra Malaysia Press 2001 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/3678/1/The_Determination_of_Pile_Capacity_Using_Artificial_Neural-net.pdf Ab. Malik, Rosely and Jamil S., Mohamed (2001) The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach. Pertanika Journal of Science & Technology, 9 (1). pp. 73-79. ISSN 0128-7680 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description From standard static formula for bearing capacity of a single pile foundation, an algorithm using a reliability approach for the determination of service load was developed. Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. In this study, the developed algorithm is further expanded to include computation of the weight-matrix of a sequential associative feedback-type neural net model for the determination of service load of a single pile is introduced. The proposed technique concludes improved efficiency over the conventional method of commissioning the functional formula of the weights by exploiting the structural properties of the matrices appeared in the codification of the service load to a single pile problem as a quadratic zero-one optimization program. Those structural attributes are distinguished and described in terms of template-matrix contributions of the constraint functions of the quadratic optimization, to the weight-matrix asynchronous auto-associative neural net It is stated by using those templates, the weight matrix can be taken in intuitively. Performance results of this research study reveal that neural net deterministic approach could be a better choice for implementation in identifying the required weight-matrix.
format Article
author Ab. Malik, Rosely
Jamil S., Mohamed
spellingShingle Ab. Malik, Rosely
Jamil S., Mohamed
The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
author_facet Ab. Malik, Rosely
Jamil S., Mohamed
author_sort Ab. Malik, Rosely
title The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
title_short The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
title_full The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
title_fullStr The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
title_full_unstemmed The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
title_sort determination of pile capacity using artificial neural-net: an optimization approach
publisher Universiti Putra Malaysia Press
publishDate 2001
url http://psasir.upm.edu.my/id/eprint/3678/1/The_Determination_of_Pile_Capacity_Using_Artificial_Neural-net.pdf
http://psasir.upm.edu.my/id/eprint/3678/
_version_ 1643822680764317696
score 13.211869

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