Neural Network Model of Phase Space and its Application in Hydrologic Mid-and-Long Term Prediction
With the frequent flood occuring and the fast economic developing in China, the flood control departments have much higher demands in watershed for the leading time and forecasting precision of flood and water resources, therefore the study of mid-and-long term runoff prediction is paid more and more attention by researchers, and it is also the most difficult problem which people are trying their best to solve. Because the hydrologic system is a complicated huge system, there exist high non-linear characteristics in the space-time change of hydrologic factors. According to theory of chaotic phase space, the paper established a mid-and-long term runoff prediction model based on the chaotic phase space and neural network. The model is applied in the long term runoff prediction of Baishan reservoir. The results of calculation show that the model has stronger non-linear mapping function and much more information in the time series than traditional ways, it is highly effective and is worthy of being popularized and applied. It is reasonable and superior to use the model in mid-and-long term hydrologic prediction.
chaos phase space neural network model mid - and - long term prediction
Zhang Liping Song Xingyuan Li Wujie Shen Tieyuan Peng Too
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Wuhan Institute of Heavy Rain, China Meteorological Administrator,Wuhan, 430074, China
国际会议
郑州
英文
1637-1641
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）