基于遗传算法的RBF神经网络的优化与应用

摘要

神经网络在处理现实问题时经常会遇到数据量大,网络结构复杂的问题,主要表现在各网络层之间权值的选取与量化和难以寻找到权值的最优解,对于RBF神经网络问题显得更为突出.针对上述问题,将遗传算法引入到RBF神经网络优化与应用当中进行论述,并将两者的结合运用于现实的问题处理当中.%neural network often encounters the difficulties of large quantity of data and the network structure is complex when deal with the practical question,it can be seen at weight number' selection and quantification and it is difficulty to find the optimal solution between network layers,it is more prominent to RBF neural network. So this essay combines the GA to RBFneural network to these prombles, and uses it in the practical question.