The prediction of damage condition in regards to damage factor influence of light structures on expansive soils in Victoria, Australia
Download
Download
Download
Full text for this resource is not available from the Research Repository.
Export
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 |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)