贝叶斯判别分析在中长期径流预报中的应用研究

基于贝叶斯判别分析原理,考虑径流形成的特点及物理成因,选择研究区碧流河水库1959~2011年的实测资料,且将径流分为5个级别,用相关系数模型,考虑因子的不确定性,筛选出相关性高、彼此间独立性强的10个判别因子,分别构建基于朴素贝叶斯分类器(N-Bayes)和贝叶斯判别准则(DBayes)的年径流属性级别预报模型,并利用研究区2001~2011年资料进行了试报和检验。预报结果表明:两种模型的预报结果相近,准确率均超过70%,D-Bayes的预报效果略优于N-Bayes,初步说明:贝叶斯判别分析原理在水文预报中的应用,有着较好的前景。

Application of Bayesian Discriminant Analysis Theory in Medium- and Long-term Hydrological Forecast

The objective of this paper is to test the application effect of Bayesian discriminant analysis theory in the annual runoff of Biliu reservoir forecasting. The proposed models are called Naive Bayesian classifier (N-Bayes) and Bayesian Discriminance criterion (D-Bayes), The structure of the paper is as follows: 1) according to the result of clustering analysis and actual conditions, the range of the runoff is divided to five levels that are deficient water, Partial deficient water, medium water, Partial abundant water and abundant water respectively; 2) selecting ten classification predictors as the correlation coefficients method and establishing runoff forecasting models of Biliu reservoir by considering the characteristic and physical genesis of runoff; 3) the forecasting models were experimented and tested by use of the data during 2001 to 2010. The result is compared with the practical attribute category shows that the accuracy of N-Bayes and D-Bayes are more than 0.7, the D-Bayes is superior to the N-Bayes in forecasting efficiency, both the two models can be a reference for reservoir operation management.