摘要
为了提高沙尘暴预报的准确率,在传统支持向量机模型的基础上加入了组合核函数的思想,将多项式核函数和高斯径向核函数组合起来代替传统模型中单一的核函数,提出了一种组合核函数支持向量机算法并将其应用于沙尘暴数据的分类与预警。以宁夏盐池地区为例,对其历史数据进行了大量预测实验,实验结果表明组合核函数支持向量机预报模型能准确地预报沙尘暴是否在某个地区发生,其成功界限指数比单一核函数支持向量机模型高出了大约2.79%。
To improve the correct rate of sand,dust storm forecasts, a support vector machine classifier with combined kernel function which integrates the polynomial kernel function with the Gussian radial kernel function together is presented, and then it is applied to the application of san＆dust storm warning. Taken Yanchi district in Ningxia as an example, a large number of pro- jections are made based on its historical data. The experimental results show the Support Vector Machine Model with combined kernel function can forecast whether sand-dust storm occurred in some region accurately and the successful limit index exceeds that of the traditional support vector machine model with single kernel function by nearly 2. 79%.
出处
《计算机工程与设计》
CSCD
北大核心
2014年第2期646-650,共5页
Computer Engineering and Design
基金
益性行业(气象)科研专项基金项目(GYHY201306015)
关键词
沙尘暴预警
组合核函数
支持向量机
分类
预报模型
sand-dust storm warning
combined kernel function
support vector machine
classification
forecasting model
