为更加准确有效地判别隧道围岩稳定性,引入RandWPSO-LSSVM(随机权重粒子群算法-最小二乘支持向量机)围岩极限位 移预测模型,对传统模型的隶属函数进行优化,建立围岩稳定性改进模糊概率模型。基于改进模型方法,由围岩位移预测值u、预测 位移标准差、围岩极限位移预测值U 及预测极限位移标准差即可求解隧道围岩稳定概率,并结合8 个工程算例对模型进行验证。 结果表明,改进模型解决了传统模型隶属函数存在的极限位移取值范围不合理的问题,且有效消除了隶属函数线性简化处理导致 的偏差,由其计算的稳定概率与实际情况吻合较好,围岩稳定性评价结果的可靠性更高; 将改进模型应用于实际工程的隧道围岩 稳定性判别中,计算结果能够较好地反映实际工程情况。

In order to judge the stability of tunnel surrounding rock more accurately and effectively, a kind of random weight particle swarm optimization(RandWPSO)-least squares support vector machine (LSSVM) prediction model for limit displacement is introduced. The membership function of fuzzy probability model for surrounding rock stability is optimized and then a modified model is established. The fuzzy probability of surrounding rock stability can be calculated by inputting parameters, i. e. the predictive displacement value u, the standard deviation of predictive displacement, the predictive limit displacement value U and the standard deviation of predictive limit displacement, into the modified model. The model is verified by 8 engineering practices. The results indicate that: (1) The problem of irrational limit displacement selection existing in the traditional membership function is solved and the error caused by the simplifying linearization treatment is evaded by the modified model effectively. (2) The calculated stability probability is in good agreement with the actual situation and the reliability of surrounding rock stability evaluation results is higher. (3) The improved model is applied to the evaluation of tunnel surrounding rock stability and the calculated results can reflect the actual engineering situation well.