AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS

被引：0
|
作者：
刘平
程翼宇
机构：
来源：
Journal of Zhejiang University-Science A(Applied Physics & Engineering) | 2000年 / 03期
关键词：
artificial neural network; genetic algorithms; layered feedforward neural networks;
D O I：
暂无
中图分类号：
TP183 [人工神经网络与计算];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The new genetic algorithm for training layered feedforward neural networks proposed here uses a mutation operator for performing the search behaviors of local optimization. Combining the random restart method with the local search technique, the algorithm can converge asymptotically to the optimal solution. Test with a practical example showed that the improved genetic algorithm is more efficient than the conventional genetic algorithm.
引用
收藏
页码：85 / 89
页数：5
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