Network Fault Diagnosis Model Based on Rough Set Theory
To aim at the defect that the co-existence of high redundancy and stability of the traditional network failure knowledge base is difficult, it comprehensively uses the neural network method and rough set theory to propose a network fault diagnosis model based on rough set theory, and achieves the rule acquisition in inconsistent case and learns the sample purification treatment.The algorithm has a simplified sample, strong adaptability and high fault tolerance and is not easy to fall into local minimum point and other features that can effectively deal with the noise or incompatible information in the network fault diagnosis.Experimental results show that compared with other similar methods, the use of this method to achieve the system improves the diagnostic accuracy and speed of diagnosis, which has a certain application value.
neural nenvork computer network faith diagnosis
Li Jinsuo
Xian Railway Vocational & Technical Institute Xian 710016,China
国际会议
成都
英文
461-465
2011-07-15（万方平台首次上网日期，不代表论文的发表时间）