UC Company Fault Diagnosis Management Information System Construction

Due to the particularity of complexity and running environment ofcommunication network structure, the failure rate has been relatively high, and thefailure is also a great harm. Therefore, the fault diagnosis communication networkequipment has always been an important aspect of the application of fault diagnosistechnology.Bayesian network can exist well quantified complex factors of uncertainty in thesystem, at the same time Bayesian network based machine learning algorithm to makethe system model of the intelligent well.In this paper, based on the data collected on the Bayesian network representation,learning and reasoning of fault diagnosis method, the Bayesian network and otherintelligence applied to communications network equipment. Fault diagnosis examples,the method is applied to the communication network of the system, the results showthat the method can make full use of the fuzzy information of the system and theuncertain information in the analysis of system reliability, so as to improve theefficiency of failure diagnosis.