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

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Osman, N. Y, McManus, K. J, Tran, D. H 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, 14 (2). pp. 331-343. ISSN 1232-308X

Abstract

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.

Item type Article
URI https://vuir.vu.edu.au/id/eprint/3383
Subjects Historical > FOR Classification > 0905 Civil Engineering
Historical > FOR Classification > 0907 Environmental Engineering
Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Keywords ResPubID16553, neural network model, genetic algorithm, prediction of damage condition of light structures, individual effects, interactive effects, Predicted Damage Conditions Model
Citations in Scopus 3 - View on Scopus
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