Forecasting Groundwater Level based on Wavelet Network Model combined with Genetic Algorithm

摘要：

This paper proposed an improved wavelet network model (WNM) which combined with genetic algorithm (GA) to forecast groundwater level,GA is used to determine the weights and parameters of WNM,which can avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models.Compared to WNM,our results show that the GA-WNM predictor can reduce significantly both relative mean errors and root mean squared errors of predicted groundwater level.We demonstrate the feasibility of applying GA-WNM in groundwater level prediction and prove that GA-WNM is applicable and performs well for groundwater data analysis.

关键词： wavelet network model genetic algorithm artificial neural network groundwater level

作者: Wang Li-ying Zhao Wei-guo

作者单位: College of Water Conservancy and Hydropower,Hebei University of Engineering Han Dan,056038,China

会议类型: 国际会议

会议名称: 2010 International Conference of Environment Materials and Environment Management(2010年环境材料与环境管理国际学术会议 EMEM 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 195-198

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）