水利水电科技进展2011，Vol.31Issue(2)：46-49,4.DOI:10.3880/j.issn.1006-7647.2011.02.011
基于小波消噪的参考作物腾发量RBF网络预测方法
RBF network forecast method for evapotranspiration of reference crops based on wavelet denoising
庾文武1
作者信息
- 1. 大唐观音岩水电开发有限公司,云南,昆明,650011
- 折叠
摘要
Abstract
The principles and procedures of the wavelet denoising were introduced. By using the daily meteorological data of a station in a northern river basin from 2001 to 2005 as the basic information, the daily meteorological data were denoised by the tenth order Dmey wavelet. A feed-forward neural network forecast model for evaportranspiration of reference crops (RBF-ET0) was established. The meteorological data from 2001 to 2004 were taken as the training samples. The evaportranspirafion of the reference crops in 2005 was predicted and compared with that calculated by the Penman-Montieth formula. The results show that the correlattion coefficient of the predicted value and the target value is 0.991 2, and the average relative error is 6.56％. The qualified rates of the relative error less than 20％, 15％ and 10％ are 93.88％, 85.66％ and 73.51％ respectively. The prediction accuracy is obviously improved compared with that by the pure RBF-ET0 model.关键词
参考作物腾发量/小波消噪/RBF网络/ET0预测方法Key words
reference crop evapotranspiration/ wavelet denoising/ RBF network/ evapotranspiration forecast method分类
建筑与水利引用本文复制引用
庾文武..基于小波消噪的参考作物腾发量RBF网络预测方法[J].水利水电科技进展,2011,31(2):46-49,4.
