摘要
针对网络工程应用性能问题,提出了基于遗传算法的前馈多层神经网络结构自动设计方法(geneticmultilayerneuralnetwork,GMNN).该方法依据网络综合性能指标(泛化能力,学习精度,学习效率)优化趋势进行网络结构优化设计.该方法具有训练速度快,适应性强的特点,对提高网络的应用性能有可取之处.仿真结果表明该方法是可行的.
Aiming at the question of neural network's application performance.This paper proposes the new method,which can automatically optimize the GMNN's structure according to the optimizing trend of ANN's comprehensive performance index(generation capability,study precision and effi-ciency).This method,having the superiority of high training speed and fitness,is able to improve the ANN's application performance.The simulation demonstrates that this method is effective.
出处
《南方冶金学院学报》
2002年第2期45-49,共5页
Journal of Southern Institute of Metallurgy
关键词
多层前向网络
遗传算法
性能函数
网络应用性能
Multilayer neural network
GA
optimizing function
ANN's application performance