Title :
Prediction of Ground Water Level Based on DE-BP Neutral Network
Author :
Ma, Lishan ; Yuan, Dekui ; Tao, Jianhua ; Yang, Guoli ; Sun, Yong
Author_Institution :
Sch. of Mech. Eng., Tianjin Univ., Tianjin, China
Abstract :
The continuous decline of ground water level is one of the important factors that affect development of national economy and society. Based on the DE-BP (back propagation-differential evolution) neutral network, the predicting model of ground water level is presented. The precision of the model is checked using the monitoring data in Zhangjiakou area. The comparisons between the predicted results of the three models (BP model, GA-BP model and DE-BP model) and the monitoring data show that the precision of the present algorithm is high with the maximum relative error being 0.17%.
Keywords :
backpropagation; environmental science computing; groundwater; neural nets; water resources; DE-BP neutral network; Zhangjiakou area; back propagation; differential evolution; ground water level prediction; model precision; monitoring data; national economy development; Artificial neural networks; Civil engineering; Economic forecasting; Environmental economics; Mechanical engineering; Monitoring; Neural networks; Predictive models; Sun; Water resources; DE-BP neutral network; ground water level; prediction;
Conference_Titel :
Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3682-8
DOI :
10.1109/ESIAT.2009.27
