基于遗传算法的应急广播传输网络故障诊断方法

为了保证应急广播的安全稳定应用,对故障问题及时诊断十分必要,本文提出一种基于遗传算法优化传输神经网络故障诊断方法,对此方法的流程加以介绍基础上,展开应急广播传输网络故障诊断仿真分析。发现此种故障诊断方法用于应急广播传输网络故障诊断中,发挥神经网络拓扑结构优势,利用遗传算法对应急广播传输网络权值、阈值进行训练,多次迭代交叉、变异后可得稳定权值、阈值,并将相应赋值作为神经网络初始值重复训练。这样的故障诊断方法能够结合遗传算法与神经网络的优势,混合算法可以获得全局最优解,改善应急广播的传输故障诊断精度与速度。

In order to ensure the safe and stable application of emergency broadcasting,it is necessary to diagnose fault problems in time.This paper proposes a fault diagnosis method based on genetic algorithm optimization of transmission neural network.Diagnostic simulation analysis.It is found that this fault diagnosis method is used in the fault diagnosis of emergency broadcast transmission network.Taking advantage of the neural network topology,the genetic algorithm is used to train the weights and thresholds of the emergency broadcast transmission network,and stable weights can be obtained after multiple iterations of crossover and mutation.,threshold,and repeat the training with the corresponding assignment as the initial value of the neural network.Such a fault diagnosis method can combine the advantages of genetic algorithm and neural network,and the hybrid algorithm can obtain the global optimal solution and improve the transmission fault diagnosis accuracy and speed of emergency broadcast.