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Design of Jetty Piles Using Artificial Neural Networks
Joint Authors
Lee, Yongjei
Lee, Sungchil
Bae, Hun-Kyun
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
To overcome the complication of jetty pile design process, artificial neural networks (ANN) are adopted.
To generate the training samples for training ANN, finite element (FE) analysis was performed 50 times for 50 different design cases.
The trained ANN was verified with another FE analysis case and then used as a structural analyzer.
The multilayer neural network (MBPNN) with two hidden layers was used for ANN.
The framework of MBPNN was defined as the input with the lateral forces on the jetty structure and the type of piles and the output with the stress ratio of the piles.
The results from the MBPNN agree well with those from FE analysis.
Particularly for more complex modes with hundreds of different design cases, the MBPNN would possibly substitute parametric studies with FE analysis saving design time and cost.
American Psychological Association (APA)
Lee, Yongjei& Lee, Sungchil& Bae, Hun-Kyun. 2014. Design of Jetty Piles Using Artificial Neural Networks. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049491
Modern Language Association (MLA)
Lee, Yongjei…[et al.]. Design of Jetty Piles Using Artificial Neural Networks. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1049491
American Medical Association (AMA)
Lee, Yongjei& Lee, Sungchil& Bae, Hun-Kyun. Design of Jetty Piles Using Artificial Neural Networks. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049491
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049491