| A RBF Network Learning Scheme Using Immune Algorithm Based on Information Entropy |
| |
| 作者姓名： | 宫新保 臧小刚 周希朗 |
| |
| 作者单位： | DepartmentofElectronicEngineering,ShanghaiJiaotongUniversity,Shanghai200030 |
| |
| 摘 要： | A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the structure and parameters of RBF nonlinear hidden layer, and weights of RBF linear output layer are computed with least square method. By introducing the diversity control and immune memory mechanism, the algorithm improves the efficiency and overcomes the immature problem in genetic algorithm. Computer simulations demonstrate that the RBF networks designed in this method have fast convergence speed with good performances.
|
| 关 键 词： | 知识工程 RBF网络 非线性近似值 学习速度 信息量 最小二乘方法 |
A RBF Network Learning Scheme Using Immune Algorithm Based on Information Entropy |
| |
| GONG Xin-bao,ZANG Xiao-gang,ZHOU Xi-lang.A RBF Network Learning Scheme Using Immune Algorithm Based on Information Entropy[J].Journal of Donghua University,2005,22(1):37-40. |
| |
| Authors: | GONG Xin-bao ZANG Xiao-gang ZHOU Xi-lang |
| |
| Abstract: | A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the structure and parameters of RBF nonlinear hidden layer, and weights of RBF linear output layer are computed with least square method. By introducing the diversity control and immune memory mechanism, the algorithm improves the efficiency and overcomes the immature problem in genetic algorithm. Computer simulations demonstrate that the RBF networks designed in this method have fast convergence speed with good performances. |
| |
| Keywords: | radial basis function networks immune algorithm least square method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
