The establishment and application of dynamic prediction model of groundwater level based on intelligent algorithm
Yongjian Liu · Shuiwen dizhi gongcheng dizhi · 2004
Underground water system is a highly complex one. There is a nonlinear relationship between underground water level and its major influential factors. This paper analyzes the shortcoming of BP neural networks and the characteristic of genetic algorithm. On the basis of the hydrologic characteristic, the major factors concerning underground water level are derived, and a dynamic prediction model of underground water level is built, which is used in a specific water resource spot. The case study shows that the model has quick convergence speed and high prediction precision as well as wide practicability in the engineering.