水利水电科技进展2016，Vol.36Issue(4)：65-69,79,6.DOI:10.3880/j.issn.1006-7647.2016.04.012
基于朴素贝叶斯算法的流域降水预测方法
A precipitation forecasting method for a river basin based on naive Bayes algorithm
摘要
Abstract
In order to effectively use available historical observation data for precipitation forecasting in the case of an uncertain cause of precipitation, a precipitation forecasting method was developed based on the naive Bayes algorithm. Using the Dongjiang Basin as an example, a rich set of features was constructed based on the basin’ s precipitation data and meteorological knowledge. The forecasting accuracy of the proposed method was compared with those of the traditional time series method and the BP neural network method. The result shows that the proposed method outperformed both the traditional time series method and the BP neural network method.关键词
降水预测/朴素贝叶斯算法/贝叶斯估计/F-measure评价方法Key words
precipitation forecasting/naive Bayes algorithm/Bayes estimation/F-measure evaluation method分类
建筑与水利引用本文复制引用
黄炜,李雪真,赵嘉,赵丽华,李臣民..基于朴素贝叶斯算法的流域降水预测方法[J].水利水电科技进展,2016,36(4):65-69,79,6.基金项目
国家自然科学基金(71433003,51179047) （71433003,51179047）
“十二五”国家科技支撑计划(2015BAB07B01) （2015BAB07B01）
