| 基于优化支持向量机的网络化制造安全检测 |
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| 引用本文： | 施进发,李济顺,焦合军,李晓东.基于优化支持向量机的网络化制造安全检测[J].兰州理工大学学报,2008,34(6). |
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| 作者姓名： | 施进发 李济顺 焦合军 李晓东 |
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| 作者单位： | 1. 郑州航空工业管理学院,河南,郑州,450015
2. 河南科技大学,机电工程学院,河南,洛阳,471003 |
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| 基金项目： | 河南省科技攻关项目
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河南省高校杰出科研人才创新工程项目
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| 摘 要： | 研究适用于小样本模式识别的新的通用学习方法最小二乘支持向量机,提出一种优化LS-SVM参数选择的方法.建立网络化制造安全检测多元分类模型,并进行仿真研究.结果表明:优化支持向量机具有优秀的小样本数据学习能力和预测能力,将其用于网络化制造安全检测是有效的、可行的.
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| 关 键 词： | 支持向量机 网络化制造 参数选择 仿真 |
Security detection of networked manufacturing based on optimized support vector machine |
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| SHI Jin-fa,LI Jis-hun,JIAO He-jun,LI Xiao-dong.Security detection of networked manufacturing based on optimized support vector machine[J].Journal of Lanzhou University of Technology,2008,34(6). |
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| Authors: | SHI Jin-fa LI Jis-hun JIAO He-jun LI Xiao-dong |
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| Institution: | SHI Jin-fa1,LI Ji-shun2,JIAO He-jun2,LI Xiao-dong2(1.Zhengzhou Institute of Aeronautical Industry Management,Zhengzhou 450015,China,2.College of Mechano-Electronic Engineering,Henan University of Science , Technology,Luoyang 471003,China) |
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| Abstract: | A new machine learning method suitable for small-sample pattern recognition,called as least square support vector machine, was investigated and the optimization method for selecting the parameters of least square support vector machines was presented.Then a security detection model of multicomponent classification for networked manufacturing was built up and the model was used for simulation investigation.The simulation results showed that the optimized support vector machine exhibited excellent ability in ... |
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| Keywords: | support vector machine networked manufacturing parameters selecting simulation |
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