STUDY ON PARALLEL EVOLUTIONARY NEURAL NETWORK FEM ON STABILITY AND OPTIMIZATION FOR LARGE CAVERN GROUPS——PART Ⅱ: CASE STUDY
大型洞室群稳定性与优化的并行进化神经网络有限元方法研究--第二部分:实例研究

A case history study on replacement scheme optimization and stability analysis of soft rock mass at a Shuibuya underground power house is presented using the proposed parallel evolutionary neural network FEM. The results indicate that the presented methodology is superior in global searching and quick convergence. The case history study gives the optimum replacement scheme and replacement steps. Through the comparison between the FEM and neural network calculation of the optimum scheme,the methodology is tested to be reasonable. Meanwhile,the rational suggestion is proposed to guide the construction.