基于演化思想的RBF神经网络优化设计

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (1): 94-94.

基于演化思想的RBF神经网络优化设计

王银坤,王学奇,肖明清,游培寒

空军工程大学工程学院

收稿日期:2005-12-30 修回日期:1900-01-01 出版日期:2007-01-01 发布日期:2007-01-01
通讯作者: 王银坤 race_wyk72

Optimization of RBF Neural Network Based on Evolvement Ideology

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空军工程大学工程学院

Received:2005-12-30 Revised:1900-01-01 Online:2007-01-01 Published:2007-01-01

摘要/Abstract

摘要： 基于事物演化发展的思想，尝试对传统RBF神经网络的结构进行了优化。首先从IPL算法对RBF网络的学习训练不足出发，通过调整RBF神经网络基函数的采样算子，得到一个规模可以控制的网络模型，最后给出了仿真验证结果。

关键词: 演化　优化　IPL算法　RBF神经网络

Abstract: Evolvement is a basic property of things development and consists of a series of complex change activities. Based on this fact, this paper focuses on providing a viable alternative for RBF network. First, aiming at the Incremental Projection Learning(IPL) algorithm’s disadvantage, the improved IPL algorithm for constructing RBF network based on the adjustment of the sampling operator is presented, and induces a simpler network structure than before. The simulation result demonstrates the effectives of the improved RBF network.

Key words: Evolvement, optimization, IPL Algorithm, RBF network

王银坤,王学奇,肖明清,游培寒. 基于演化思想的RBF神经网络优化设计[J]. 计算机工程与应用, 2007, 43(1): 94-94.

,,,. Optimization of RBF Neural Network Based on Evolvement Ideology[J]. Computer Engineering and Applications, 2007, 43(1): 94-94.