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多层RBF网络的自适应遗传算法及其在实函数逼近中的应用
引用本文:盛飞,庄健. 多层RBF网络的自适应遗传算法及其在实函数逼近中的应用[J]. 安徽工业大学学报, 2013, 30(2): 192-196,202
作者姓名:盛飞  庄健
作者单位:安徽工业大学经济学院,安徽马鞍山,243032
摘    要:将自适应遗传算法应用于多层RBF神经网络的学习,对隐层核函数的中心和宽度值进行同时优化,并用正则最小二乘法求权重,以完成网络的构建。应用该学习法进行实函数的逼近,实验证明了该算法比多层RBF网络的聚类学习法具有更高的实函数逼近精度。

关 键 词:多层RBF神经网络  自适应遗传算法  实函数逼近

Adaptive Genetic Algorithm for Multilayer RBF Network and It's Application on Real Function Approximation
SHENG Fei , ZHUANG Jian. Adaptive Genetic Algorithm for Multilayer RBF Network and It's Application on Real Function Approximation[J]. Journal of Anhui University of Technology, 2013, 30(2): 192-196,202
Authors:SHENG Fei    ZHUANG Jian
Affiliation:(School of Economics, Anhui University of Technology, Ma'anshan 243032, China )
Abstract:With the application of adaptive genetic algorithm to the training of multi-layer RBF networks and the optimization of the hidden layer centers and width values and using regularized least squares method, weight vectors is obtained. Computer simulation shows that the precision of real function approximation by this algorithm is much higher than the precision by clustering algorithm for multi-layer RBF networks.
Keywords:multilayer RBF network  adaptive genetic algorithm  approximation of real function
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