基于粗糙集和BP神经网络算法的网络故障诊断模型研究
PDF下载 (391)尚志信,周 宇,叶庆卫,王晓东.基于粗糙集和BP神经网络算法的网络故障诊断模型研究[J].宁波大学学报(理工版),2013,26(02):45-48.DOI:
SHANG Zhi-xin,ZHOU Yu,YE Qing-wei,WANG Xiao-dong.Network Fault Diagnosis Based on Rough Sets and BP Neural Network[J].Journal of Ningbo University(Natural Science & Engineering Edition),2013,26(02):45-48.DOI:
| Title: | Network Fault Diagnosis Based on Rough Sets and BP Neural Network |
| 作者: | 尚志信, 周 宇, 叶庆卫, 王晓东 |
| Author(s): | SHANG Zhi-xin, ZHOU Yu, YE Qing-wei, WANG Xiao-dong |
| 关键词: | 粗糙集; BP神经网络; 网络故障诊断; 知识库 |
| Keywords: | rough set; BP neural network; network fault diagnosis; knowledge base |
| 分类号: | TP391 |
| 文献标识码: | A |
| 摘要: | 针对计算机网络故障诊断知识库冗余性高、神经网络与PCA、DS证据等理论相结合诊断精度不高的难题, 提出了一种新的基于粗糙集和BP神经网络的计算机网络故障诊断模型. 首先利用粗糙集算法对网络故障特征进行约简处理、提取最小诊断规则; 其次利用最小规则训练BP神经网络, 建立基于粗糙集和BP神经网络的计算机网络故障诊断模型; 最后将模型运用于真实网络故障数据诊断. 结果表明: 该模型具有学习效率高、诊断速度快、准确率高的特点, 能够快速诊断网络故障类型. |
| Abstract: | To deal with the problems of redundancy of network fault diagnosis, the knowledge base and Low Accuracy of neural network model combined with PCAand DS evidence theory are presented in this paper. A new fault diagnosis model of computer network based on rough set and BP neural network is engineered, in which many fault features of computer network are retrieved. These features are then reduced to the minimum diagnosis rules using rough set. The minimum diagnosis rules are trained by BP neural network. The simulation results indicate that the new fault diagnosis model has higher learning efficiency, faster speed of diagnosis and higher detection accuracy. |
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| 备注/Memo: | 收稿日期: 2012－11－03. 基金项目: 国家自然科学基金（61141015）; 浙江省自然基金（Y1110161）; 宁波市自然科学基金（2011A610181）. 第一作者: 尚志信（1986－）, 男, 河南商丘人, 在读硕士研究生, 主要研究方向: 网络故障诊断. E-mail: xinzhishang2007@163.com *通信作者: 周 宇（1960－）, 男, 山东威海人, 教授, 主要研究方向: 网络通信及计算机软件. E-mail: zhouyu@nbu.edu.cn 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
