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基于EMD的支持向量回归机振动数据挖掘
引用本文:杨晓红,杨晓静,朱霄珣.基于EMD的支持向量回归机振动数据挖掘[J].煤矿机械,2010,31(11).
作者姓名:杨晓红  杨晓静  朱霄珣
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。

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 for Date Mining Based on Empirical Mode Decomposition
YANG Xiao-hong,YANG Xiao-jing,ZHU Xiao--xun.Support Vector Regression for Date Mining Based on Empirical Mode Decomposition[J].Coal Mine Machinery,2010,31(11).
Authors:YANG Xiao-hong  YANG Xiao-jing  ZHU Xiao--xun
Abstract: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.
Keywords:support vector regression  empirical mode decomposition  fault diagnosis  state forecast  date mining
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