云南农业大学学报2012，Vol.27Issue(2)：281-284,4.DOI:10.3969/j.issn.1004-390X(n).2012.02.025
基于BP神经网络的缺测降水数据插补
Interpolation of Missing Precipitation Data Base on BP Neural Network
摘要
Abstract
The interpolation of missing precipitation data can improve the integrity of data series effectively. We did some research on interpolation of missing precipitation data base on hydrological and rainfall station's month and annual precipitation data in Yuanjiang, Wadi, Yinyuan, Jiezihe, Azhi and Mofanghe which are in Yuanjiang area. Correlation analysis among all stations showed that: correlation among all stations in the study area was weak; correlation analysis could hardly meet the interpolation precision in some months. So we tried to use the BP neural network model to interpolate the precipitation data in study area. The research showed that; the acceptable quality level of BP neural network sample test reached 89. 6% , which showed that the BP neural network could be used to interpolate the missing precipitation data in the area which we had studied and it provided a new way to interpolate the missing precipitation data.关键词
BP网络/降水/相关分析/插补Key words
BP neural network/precipitation/correlation analysis/interpolation分类
农业科技引用本文复制引用
田琳,王龙,余航,杨蕊..基于BP神经网络的缺测降水数据插补[J].云南农业大学学报,2012,27(2):281-284,4.基金项目
水利部公益性行业专项云南旱灾应急响应系统研究(201001044-1) （201001044-1）
云南省应用基础研究面上项目(2007D210M) （2007D210M）
云南省教育厅科学研究基金重大专项项目(ZD2009010) （ZD2009010）
云南省教育厅科学研究基金(09J0076). （09J0076）
