摘要
提出了基于经验模态分解的支持向量回归机方法。该方法首先利用经验模态分解(EMD)方法对信号分解,得到若干平稳分量,然后对各分量进行回归建模,对各分量的回归结果求和得到原信号的回归结果。经实验分析验证,该方法不但提高了回归的准确度,而且运算时间也大大减少,实现了准确而又快速的拟合和预测。
Puts forward the SVR method based on the empirical mode decomposition （EMD）. This method uses the EMD to decompose the signal to get the stable components firstly. Then the regression models are set up for these components. The regression calculation of the components is added together to gain the regression result of the original signal. The experiment shows that this method not only improves the calculating precision, but also greatly reduces the computing time. Using this method, the fast and accurate data fitting and prediction can be gained.
出处
《煤矿机械》
北大核心
2010年第11期252-254,共3页
Coal Mine Machinery
关键词
支持向量回归机
经验模态分解
故障诊断
状态预测
数据挖掘
support vector regression
empirical mode decomposition
fault diagnosis
state forecast
date mining
