BP Neural Networks Model of Forecasting Sediment Discharge Based on Chaos Phase Space
Research on water and sediment production is one of the important preparatory works for basin ecological and environmental protection, river training and water resources planning. There are vast factors which influence evolvement law of sediment discharge, and these factors are very difficult to be known and gained, which results in low precision of simulation and forecast. Based on analysis on chaos characteristic of sediment discharge time series, BP neural networks model based on chaos phase space is proposed to forecast sediment discharge through embedding dimension. Considering influence of dynamical factor of sediment discharge as well as difficulty of calculating number of input cell, provided with strong nonlinear mapping capacity, the model is applied to simulate and forecast monthly sediment discharge of specific river basin, the outcomes is reasonable and has higher precision.
chaos phase space neural networks sediment discharge
Zhang Xianqi Sun Dongpo
North China University of Water Conservancy & Hydro - electric Power, Zhengzhou, 450011, China
国际会议
郑州
英文
1748-1754
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）