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The prediction of damage condition in regards to damage factor influence of light structures on expansive soils in Victoria, Australia

Osman, N. Y., McManus, K. J., Tran, H. D. and Krezel, Z. A. 2007, The prediction of damage condition in regards to damage factor influence of light structures on expansive soils in Victoria, Australia, Computer Assisted Mechanics and Engineering Sciences : CAMES, vol. 14, no. 2, pp. 331-343.

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Title The prediction of damage condition in regards to damage factor influence of light structures on expansive soils in Victoria, Australia
Author(s) Osman, N. Y.
McManus, K. J.
Tran, H. D.
Krezel, Z. A.
Journal name Computer Assisted Mechanics and Engineering Sciences : CAMES
Volume number 14
Issue number 2
Start page 331
End page 343
Publisher Polish Academy of Sciences, Institute of Fundamental Technological Research
Place of publication Warsaw, Poland
Publication date 2007
ISSN 1232-308X
Summary This paper proposes a neural network model using genetic algorithm for a model for the prediction of the damage condition of existing light structures founded in expansive soils in Victoria, Australia. It also accounts for both individual effects and interactive effects of the damage factors influencing the deterioration of light structures. A Neural Network Model was chosen because it can deal with 'noisy' data while a Genetic Algorithm was chosen because it does not get `trapped' in local optimum like other gradient descent methods. The results obtained were promising and indicate that a Neural Network Model trained using a Genetic Algorithm has the ability to develop an interactive relationship and a Predicted Damage Conditions Model.
Notes This paper was presented at the International symposium on neural networks and soft computing (NNSC-2005), Cracow, Poland, 30 June - 2 July, 2005.
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Language eng
Field of Research 090501 Civil Geotechnical Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2007, Institute of Fundamental Technological Research, Polish Academy of Sciences
Persistent URL http://hdl.handle.net/10536/DRO/DU:30007391

Document type: Journal Article
Collections: School of Architecture and Built Environment
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.