TY - EJOU AU - Yang, Fan AU - Ren, Jianwei TI - Reliability Analysis Based on Optimization Random Forest Model and MCMC T2 - Computer Modeling in Engineering \& Sciences PY - 2020 VL - 125 IS - 2 SN - 1526-1506 AB - Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. KW - Markov chain; random forest; Monte Carlo simulation; nonlinear function; random uncertainty DO - 10.32604/cmes.2020.08889