| 基于支持向量机的网络故障在线诊断方法研究 |
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| 引用本文： | 周小平,晏蒲柳,吴静. 基于支持向量机的网络故障在线诊断方法研究[J]. 武汉大学学报(工学版), 2006, 39(3): 102-106 |
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| 作者姓名： | 周小平 晏蒲柳 吴静 |
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| 作者单位： | 武汉大学电子信息学院,湖北,武汉430079 |
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| 摘 要： | 介绍了网络故障诊断的发展趋势和支持向量机的基本原理,采用一种改进的支持向量机用于网络故障的在线诊断和分析,并且以实验网中采集的数据进行了实验,实验表明该方法能够快速准确地在线诊断网络故障,为网络故障在线诊断向智能化方向发展提供了新的途径.
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| 关 键 词： | 网络故障诊断 支持向量机(SVM) 最优超平面 |
| 文章编号： | 1671-8844（2006）03-102-04 |
| 收稿时间： | 2005-12-25 |
| 修稿时间： | 2005-12-25 |
Research on network fault diagnosis method based on support vector machines |
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| ZHOU Xiaoping,YAN Puliu,WU Jing. Research on network fault diagnosis method based on support vector machines[J]. Engineering Journal of Wuhan University, 2006, 39(3): 102-106 |
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| Authors: | ZHOU Xiaoping YAN Puliu WU Jing |
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| Affiliation: | School of Electronic Information, , YAN Puliu, WU Jing Wuhan University, Wuhan 430079, China |
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| Abstract: | The basic theory of support vector machines and development tendency of network fault diagnosis are introduced. For the network fault on-line diagnosis, an improved support vector machine and experimentation with the network data from the laboratorial network are conducted. The experiments show that the method to diagnose network fault is fast and accurate;it provides us a new approach to develop the intelligent network fault diagnosis. |
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| Keywords: | network fault diagnosis support vector machine optimal hyperplane |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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