双评价粒子群算法确定非线性流含水层参数

Determination of Aquifer Parameters in Nonlinear Flow by Double Evaluation of Particle Swarm Optimization Algorithm

在标准粒子群算法的基础上,对迭代后的粒子进行位置和适应值的双评价,得到改进的粒子群优化算法。在化简非稳定井流问题解析解的基础上,利用抽水试验数据,根据最小二乘原理,确定了求解含水层参数与非线性渗流参数的目标函数,编写了用于求解该问题的双评价粒子群优化算法程序。最后,通过数字算例验证了方法的可行性和可靠性。

On the basis of particle swarm optimization, the position and fitness value of the iteration of the particles are evaluated; the modified particle swarm optimization is obtained. First, based on the simplified analysis of unsteady flows, according to the data of pumping tests and the principle of least square to determine the target function of solving aquifers and nonlinear parameters, then, the computation procedure is constructed. At last, through the numerical examples it verifies the double evaluation of particle swarm optimization algorithm is reliable and feasible.