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

• Autorzy: Osman N. Y. , McManus K. J. , Tran H. D. , Krezel Z.
• Konferencja: Neural Networks and Soft Computing/International Symposium (30.06-02.07.2005 ; Cracow, Poland)
• Języki publikacji: EN

Abstrakty

EN

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 Networlc Model trained using a Genetic Algorithm has the ability to develop an interactive relationship and a Predicted Damage Conditions Model.

Słowa kluczowe

EN

neural network; genetic algorithm

PL

sieci neuronowe; algorytm genetyczny

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2007
• Tom: Vol. 14, No. 2
• Strony: 331--343
• Opis fizyczny: Bibliogr. 26 poz., rys., tab.

Twórcy

autor

Osman N. Y.

autor

McManus K. J.

autor

Tran H. D.

autor

Krezel Z.

• Faculty of Engineering and Industrial Sciences Swinburne University of Technology, Melbourne, Australia

Bibliografia

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