The runoff forecasting model based on wavelet adaptive neural fuzzy inference system
Considering various the wavelet decomposition reconstruction technology and training cycle of adaptive neural fuzzy inference system,this article propose four runoff forecast model of wavelet analysis and adaptive neural fuzzy inference system integration,such as the long cycle based on Mallat algorithm in runoff prediction,the long cycle based on wavelet packet algorithm in runoff prediction,the short cycle based on Mallat algorithm in runoff prediction,the short cycle based on wavelet packet algorithm in runoff prediction,and illuminate the model of the principles,structures and procedures.This model is used in Tangnaihe station monthly runoff forecast which lies in the (uanghe) source area.Simulation results are evaluated by the cycle decomposition coefficients and Nash-Sutcliffe coefficient; it shows that the long cycle based on Mallat algorithm is best,the short cycle based on wavelet packet algorithm is worst.The author analyzes the reason and makes some proposal.
Wavelet analysis adaptive neural fuzzy inference system runoff forecast model
Gu Jun-fang Wang Xiao-li Du Fu-hui
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing School of Hydraulics and Electric Power,Hebei University of Engineering,Handan,Hebei 05603
国际会议
沈阳
英文
1032-1040
2012-09-07（万方平台首次上网日期，不代表论文的发表时间）