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

Abstract

In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) and Monte Carlo simulation are applied for reliability analysis of structures. The drawback of Monte Carlo Simulation is the amount of computational efforts. ANFIS is capable of approximating structural response for calculating probability of failure, letting the computation burden at much lower cost. In fact, ANFIS derives adaptively an explicit approximation of the implicit limit state functions. To this end, a quasi-sensitivity analysis in consonance with ANFIS was developed for determination of dominant design variables, led to the approximation of the structural failure probability. However, preparation of ANFIS , 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. The proposed methodology was considered applying some illustrative examples.