A Combination of Differential Evolution and Support Vector Machine for Rainstorm Forecast

被引：1

作者：

Jun, Shu ^{[1
]}

Jian, Li ^{[2
]}

机构：

[1] Hubei Univ Ind, Inst Elect & Elect Engn, Wuhan, Peoples R China

[2] Hubei Univ Educ, Dept Comp Engn, Wuhan, Peoples R China

来源：

2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 3, PROCEEDINGS | 2009年

关键词：

rainstorm forecast; differential evolution; support vector machine;

D O I：

10.1109/IITA.2009.475

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study employed a DE SVM model that hybridized the differential evolution (DE) and support vector machines (SVM) to improve the classification accuracy for rainstorm forecasting. This optimization mechanism combined the DE to optimize the SVM parameter setting. Based on the European Centre for Medium-Range Weather Forecasts (ECMWF), Japan and T213 precipitation data from 2003 to 2006, using DE SVM, the 24 hour's storm models for 5 sub-regions in Hubei province were created, which have been used in the real-time running work from May to July in 2007. The results have shown the forecasting ability and reference value of the SVM method.

引用

页码：392 / +

页数：3