基于遗传算法的一种新的神经网络结构模式研究

神经网络与遗传算法的结合为解决大规模、复杂、并行的系统问题提供了广阔的前景，但其有着固有的缺陷和不足，本文在遗传算法的基础上，提出了一种新的神经网络结构构式，它能将遗传算法与神经网络更加有机地结合起来，改进其不足，增加神经网络的学习方式，提高学习效率和网络的稳定性。

A New Neural Network Structure Pattern Based on Genetic Algorithm

Combination of Neural Networks (NN) and Genetic Algorithms (GA) has offered bright foregrounds to solve large-scale, complex and paralleling problems. But this method has intrinsic shortcomings. In this article, the authors have brought forward a new structure mode of neural networks, it can avoid efficiently the defects of the combination of NN and GA on original NN structure, and it can raise the learning efficiency, enhance learning modes as well as improve the stability of NN.