Author
Ru-cheng Xiao
Bio: Ru-cheng Xiao is an academic researcher from Tongji University. The author has contributed to research in topics: Artificial neural network. The author has an hindex of 1, co-authored 1 publications receiving 143 citations.
Topics: Artificial neural network
Papers
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TL;DR: In this article, a new artificial neural network-based response surface method in conjunction with the uniform design method for predicting failure probability of structures is presented, which involves the selection of training datasets for establishing an ANN model, approximation of the limit state function by the trained ANN model and estimation of the failure probability using first-order reliability method (FORM).
164 citations
Cited by
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TL;DR: In this article, the authors present a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis, identifying the different types of ANNs, the methods of structural reliability assessment that are typically used, the techniques proposed for ANN training set improvement and also some applications of ANN approximations to structural design and optimization problems.
278 citations
TL;DR: This work develops an efficient reliability method which takes advantage of the Adaptive Support Vector Machine (ASVM) and the Monte Carlo Simulation (MCS), leading to accurate estimation of failure probability with rather low computational cost.
190 citations
TL;DR: It is shown that there is no obvious difference between RBFN-based RSMs and SVM- based RSMs, and the number of samples needed in RBFN/SVM-RSM2 is smaller than that of RBFN /SVM/RSM1.
143 citations
TL;DR: A design optimization method based on kriging surrogate models is proposed and applied to the shape optimization of an aeroengine turbine disc to improve the accuracy of surrogate models without significantly increasing computational cost.
115 citations
TL;DR: In this paper, the authors use accurate and efficient means to evaluate system reliability again and optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, and it is essential to use accurate, efficient, and accurate means for evaluating system reliability.
Abstract: To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability again...
104 citations