水利水电技术2011，Vol.42Issue(4)：71-73,76,4.
基于支持向量机模型的湘江枯水预报研究
Support vector machine model based study OH low-water forecast of Xiangjiang River
摘要
Abstract
Along with the increasing problem of water shortage during the dry period, more and more attentions are paid upon the study of low-water runoff. The minimum annual mean flow rate/7days of Xiangtan Hydrological Station of Xiangjiang River is forecasted herein based on the support vector machines model. In order to check the forecast effect, the forecast result is compared with the forecast results from both the projection pursuit model and the artificial neural networks model. It is indicated that the qualified rate of the error from the support vector machine model is highest, and then its forecast precision is highest as well关键词
支持向量机/预报精度/枯水预报/湘江Key words
support vector machine/ forecast precision/ low-water forecast/ Xiangjiang River分类
天文与地球科学引用本文复制引用
石月珍,徐冬梅..基于支持向量机模型的湘江枯水预报研究[J].水利水电技术,2011,42(4):71-73,76,4.基金项目
水沙科学与水灾害防治湖南省重点实验室"湘江流域洪水资源利用模式及风险分析"(2010SS06). （2010SS06）
