CAJ | 학술논문

本文在神经网络训练过程中，加入一个局部极小判别式，以确定网络是否陷入局部极小点，若陷入局部极小点，则利用遗传算法进行权值修正。以鼓风机常见故障为例，应用本文提出的遗传神经网络算法对其进行了故障诊断分析，从而证明了该算法的有效性。
본문재신경망락훈련과정중，가입일개국부겁소판별식，이학정망락시부함입국부겁소점，약함입국부겁소점，칙이용유전산법진행권치수정。이고풍궤상견고장위례，응용본문제출적유전신경망락산법대기진행료고장진단분석，종이증명료해산법적유효성。
Aiming at the problems of slow rate of convergence and falling easily into part minimums in BP algorithm, a new improved genetic BP algorithm was put forward. To determine whether the network fall into part minimum point,a discriminant of part minimum was put forth in the training process of neural network. Genetic algorithm was used to revise the weights of the neural network if the BP algorithm fell into minimums. The blower faults were diagnosed using the algorithm put forward in this paper, which testified the validity of this improved genetic BP algorithm.