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


Autoria(s): Osman, N. Y.; McManus, K. J.; Tran, H. D.; Krezel, Z. A.
Data(s)

01/01/2007

Resumo

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.<br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30007391

Idioma(s)

eng

Publicador

Polish Academy of Sciences, Institute of Fundamental Technological Research

Relação

http://dro.deakin.edu.au/eserv/DU:30007391/osman-thepredictionof-2007-abstract.pdf

http://cames.ippt.gov.pl/

Direitos

2007, Institute of Fundamental Technological Research, Polish Academy of Sciences

Tipo

Journal Article