Synchronization Optimization Simulation of Optical Fiber Network Fault Features and Model Parameters

Abstract

The traditional optical fiber network fault detection method has not considered the relationship between the fault characteristics and KNN parameters, it is optimized separately, and the accuracy of optical fiber network fault diagnosis is low. The synchronous optimization fault detection model of fault characteristics detection model parameters is proposed. The candidate feature subsets and K adjacent parameters are used to construct the optical fiber network fault detection model. The improved genetic algorithm is used to solve the mathematical model, and the better accurate rate of fault diagnosis for optical fiber network is obtained. The simulation is taken for testing the performance of model, compared to the traditional model, the new model has better accurate detection rate, and the detection accuracy is improved greatly, the efficiency of optical fiber network fault detection is improved, it has great application value in practice.