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岩石蠕变模型的参数较多,为得到参数的全局最优解,应用微进化算法(Microevolution Algorithm,MA)对岩石蠕变模型非定常参数进行了反演分析。算法以实测蠕变值与理论计算值之间的最小二乘误差为优化准则函数,直接反演计算蠕变模型参数。计算结果表明,微进化算法可最大限度地利用所有试验数据,避免传统优化算法初始参数选取的困难,且算法简单有效,计算精度高于混沌粒子群优化算法。该方法也可推广应用于其它蠕变模型的参数反演,具有较高的工程应用价值。
There are many parameters of rock creep model. To obtain the global optimal solution of parameters, the unsteady parameters of rock creep model are inversely analyzed by Microevolution Algorithm (MA). The algorithm takes the least square error between the measured creep value and the theoretical value as the optimization criterion function and directly inverts the creep model parameter. The calculation results show that the micro-evolution algorithm can make full use of all the experimental data to avoid the difficulty of selecting the initial parameters of the traditional optimization algorithm, and the algorithm is simple and effective, and the calculation accuracy is higher than the chaotic particle swarm optimization algorithm. The method can also be widely applied to the inversion of parameters of other creep models and has high engineering application value.