Mathematical Model of Short Circuit Fault Diagnosis in management and collaborative System Based On Improved SOM Neural Network

Abstract

The existing mathematical model for short-circuit fault diagnosis of management and collaborative system has the problem that the session characteristics of communication link are not clear, resulting in the slow upload speed of fault data. In order to solve this problem, a short-circuit fault diagnosis mathematical model of communication system based on improved SOM neural network and the innovative strategies also management and collaborative system is describe in this paper. Firstly, the early warning information of the system is collected, combined with the repeated information, the session characteristics of the communication link are extracted by using the quasi Newton algorithm, the mutually orthogonal physical resource blocks are transformed, the short-circuit fault diagnosis mode is optimized, the parameters of the components to be detected are estimated, the feature space vector is truncated, and the mathematical model is established by using the improved SOM neural network. Experimental results: the average value of the management and collaborative system short-circuit fault diagnosis mathematical model designed in this paper is 8.244 Mbps, and the average values of the other two management and collaborative system short-circuit fault diagnosis mathematical models are 5.756 Mbps and 5.863 Mbps respectively. The results show that the designed mathematical model for short circuit fault diagnosis of management and collaborative system has high application value.