DocumentCode
2895660
Title
Structural Reliability Analysis Based on Neural Network and Finite Element Method
Author
Duan, Wei ; Chen, Li-xin ; Wang, Zhang-Qi
Author_Institution
Sch. of Mech. Eng., North China Electr. Power Univ., Baoding
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
3063
Lastpage
3068
Abstract
A new approach for structural reliability analysis with implicit performance function is presented by combining the neural network, finite element method (FEM) and first-order reliability method (FORM). BP network is applied to approximate the implicit performance function, which is more flexible and adaptive than the polynomial function used in response surface method. The first derivatives of the performance function with respect to random variables can be obtained by the successful trained BP network, which plays an important role in calculating the reliability index. The training samples come from the numerical results of FEM. Two examples are given to demonstrate the validity of the method. The method can be applied to the structural reliability analysis with implicit performance function
Keywords
backpropagation; finite element analysis; neural nets; polynomials; reliability theory; response surface methodology; structural engineering computing; BP network; finite element method; first-order reliability method; neural network; polynomial function; response surface method; structural reliability analysis; Analytical models; Artificial neural networks; Cybernetics; Electronic mail; Finite element methods; Machine learning; Mechanical engineering; Neural networks; Neurons; Performance analysis; Random variables; Response surface methodology; BP neural network; Structural reliability analysis; finite element method; first-order reliability method;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258367
Filename
4028590
Link To Document