Reliability and Sensitivity Analysis of Structures Using Adaptive Neuro-Fuzzy Systems

Document Type: Regular Paper


1 Assistant Professor, Department of Civil Engineering, Payame Noor University (PNU), 19395-3697 Tehran, I.R. of Iran

2 Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, 9816745437, Iran


In this study, an efficient method based on Monte Carlo simulation, utilized with Adaptive Neuro-Fuzzy Inference System (ANFIS) is introduced for reliability analysis of structures. Monte Carlo Simulation is capable of solving a broad range of reliability problems. However, the amount of computational efforts that may involve is a draw back of such methods. ANFIS is capable of approximating structural response for predicting probability of failure, allowing the computation of performance measures at much lower cost. In fact, ANFIS derives adaptively an explicit approximation of the implicit limit state functions. For this purpose, a quasi sensitivity analysis based on ANFIS was developed for determination of most influential design variables, used for predicting the limit state function, led to the approximation of the structural failure probability. Preparation of ANFIS however, was preceded using a relaxation based method developed by which the optimum number of training samples and epochs was obtained. That was introduced to more efficiently reduce the computational time of ANFIS training. To assess the effectiveness of the proposed methodology, some illustrative examples are considered.


Main Subjects

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