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利用水头实测资料,以裂隙组的渗透系数比例因子为待反演的参数向量,在采用基本遗传算法进行参数反演研究的基础上,针对裂隙岩体无压渗流参数反问题计算量过大,目标参数众多以及参数可能变化范围大等特点,提出了一种混合遗传算法求解此类问题,力求克服简单遗传算法在解决此类问题时存在的局部搜索能力弱、易出现早熟收敛及计算量大等缺陷,并通过典型岩坡渗流算例进行验证,同时给出了基本遗传算法、传统单纯形算法的反演成果。计算结果表明,该方法保持了基本遗传算法优点,并有效地提高了算法的运行效率,从而为求解裂隙岩体无压渗流参数反问题等计算量大的系列问题提供了新的途径。
Based on the measured data of the head and the parameters of the permeability coefficient of the fracture group, the parameter vectors to be inverted are studied. Based on the inversion of the parameters by the basic genetic algorithm, the calculation of the inverse problem of the pressureless seepage flow in the fractured rock mass is too large, A large number of target parameters and a large range of parameters, a hybrid genetic algorithm (GA) is proposed to solve this kind of problem and tries to overcome the shortcoming of simple genetic algorithm in solving such problems, such as weak local search ability, premature convergence and large amount of calculation And other defects, and verified by the example of typical seepage of rock slope. At the same time, the basic genetic algorithm and the inversion result of the traditional simplex algorithm are given. The calculation results show that the proposed method preserves the advantages of the basic genetic algorithm and improves the efficiency of the algorithm effectively. Therefore, this method provides a new approach for solving the large computational problems such as the inverse problem of pressureless seepage flow in fractured rock masses.