关键词: 遗传算法, 高斯牛顿法, 联合反演方法, 地下水数值模型, 参数

Abstract: A genetic algorithm (GA) searches in the whole solving space as it deals with nonlinear optimization problems. But in the local solving space, GA is slow and the solution precision is low. The Gauss-Newton Method (GNM) has inverse characters on these points. In this paper, the GA and GNM are used in the parameter identification of ground water flow. GA solves the initial values of parameters. And then, the parameters are identified by GNM. We take 3-dimensional unsteady state flows in an inhomogeneous isotropic confined aquifer as an ideal model, and discuss application of GA and GNM to inverse problem of hydrogeology parameters with finite element method. It is shown that the improved algorithm converges faster and provides higher precision.

Key words: genetic algorithm, Gauss-Newton method, united inversing method, groundwater flow numerical model, parameters