Back analysis of microplane model parameters using soft computing methods

• Autorzy: Kučerová A. , Lepš M. , Zeman J.
• Konferencja: Neural Networks and Soft Computing/International Symposium (30.06-02.07.2005 ; Cracow, Poland)
• Języki publikacji: EN

Abstrakty

EN

A new procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a systematic employment of stochastic sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed.

Słowa kluczowe

EN

neural network; soft computing methods; artificial neural networks; microplane model

PL

sztuczne sieci neuronowe; sieci neuronowe

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2007
• Tom: Vol. 14, No. 2
• Strony: 219--242
• Opis fizyczny: Bibliogr. 15 poz., il., tab., wykr.

Twórcy

autor

Kučerová A.

autor

Lepš M.

autor

Zeman J.

• Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague Thákurova 7, 166 29 Prague 6, Czech Republic

Bibliografia

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