Reliability analysis using artificial neural networks

A probabilistic analysis approach is developed by extending the Monte Carlo simulation. The Multilayer perceptron with backpropagation learning algorithm is applied in reliability analysis as the substitute of finite element solver. The reliability of a tunnel is analyzed as an example. Through Mont...

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Vydané v:2010 Sixth International Conference on Natural Computation Ročník 4; s. 1783 - 1787
Hlavní autori: Changqing Qi, Jimin Wu
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.08.2010
Predmet:
Artificial neural networks
backpropagation learning algorithm
Finite element methods
Geology
Monte Carlo methods
Monte Carlo simulation
multilayer perceptron
Reliability
reliability analysis
stochastic finite element method
Stochastic processes
Training
ISBN:1424459583, 9781424459582
ISSN:2157-9555
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Popis
Shrnutí:A probabilistic analysis approach is developed by extending the Monte Carlo simulation. The Multilayer perceptron with backpropagation learning algorithm is applied in reliability analysis as the substitute of finite element solver. The reliability of a tunnel is analyzed as an example. Through Monte Carlo simulations, the input and output samples of the network are obtained. As comparing to the responses obtained by Monte Carlo simulations with finite element solver, the network performs high accuracy and fast training speed. The results show that the proposed approach is a promising tool for stochastic analysis inasmuch as the error with respect to finite element solver is negligible.
ISBN:1424459583
9781424459582
ISSN:2157-9555
DOI:10.1109/ICNC.2010.5584442