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.
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. 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
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