Application of rough set theory in network fault diagnosis

In this paper rough set theory is researched and applied in computer network fault diagnosis. Original MIB( information base of management) data from network which reflect network fault are collected first, and a reduction algorithm based on attribute significance and attribute frequency is implemented on the MIB data, which removing inconsistent or erroneous MIB data. Based on attribute core and user preference attribute set, the algorithm makes not only use of advantage of these two algorithm, but also the universality of core, user background knowledge, and domain experience. At the same time, the minimal support degree and minimal belief degree is introduced into rough set theory for decision rules discovery and get decision rules.