摘要: 反向传播算法的最大缺陷之一是容易陷入局部极小点.为此,我们在基因遗传算法(GA)原理的基础上,增加了区域变化这一重要环节,设计出一种新的启发式遗传操作算法,并将它用于多层神经网络的学习过程.实例结果表明用此算法能快速得到最佳权值分布.
关键词:
GA,
多层神经网络,
区域变化,
最优
Abstract: One of the main weak-points of back propagation algorithm of multi-layer neural network is that the optimal procedure is easily stacked into the minimal value locally.Based on the genetic algorithm(GA), a new huristic genetic algorithm is presented which includes an important procedure called searching region chane / re-duction andis of higher efficiency as compared with general genetic algorithm.
In this paper, the algorithm is applied in the weights study of multi-layer neural network, and results in fast optimal weights
韦柳涛,钱治航,夏金安,虞锦江,刘育骐,管家宝. 基于遗传交换操作的多层神经网络算法[J]. , 1993, 19(06): 26-29.
Wei Liutao. A MULTI-LAYER NEURAL NETWORK ALGORITHM BASED ON THE NEW HURISTIC GENETIC ALGORITHM[J]. , 1993, 19(06): 26-29.