华南理工大学学报(自然科学版) ›› 2009, Vol. 37 ›› Issue (1): 86-90.

• 电子、通信与自动控制 • 上一篇    下一篇

基于新型进化规划的异构神经网络集成算法

王立 朱学峰   

  1. 华南理工大学 自动化科学与工程学院, 广东 广州 510640
  • 收稿日期:2008-01-16 修回日期:2008-03-03 出版日期:2009-01-25 发布日期:2009-01-25
  • 通信作者: 王立(1980-),女,博士生,主要从事模式识别、机器学习研究. E-mail:wli1129@163.com
  • 作者简介:王立(1980-),女,博士生,主要从事模式识别、机器学习研究.
  • 基金资助:

    广东省科技攻关项目(2005B10201005)

Algorithm of Heterogeneous Neural Network Ensemble Based on New Evolutionary Programming

Wang Li  Zhu Xue-feng   

  1. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2008-01-16 Revised:2008-03-03 Online:2009-01-25 Published:2009-01-25
  • Contact: 王立(1980-),女,博士生,主要从事模式识别、机器学习研究. E-mail:wli1129@163.com
  • About author:王立(1980-),女,博士生,主要从事模式识别、机器学习研究.
  • Supported by:

    广东省科技攻关项目(2005B10201005)

摘要: 为了进一步提高集成算法的泛化性能,增强个体网络生成过程的客观性,提出一种基于新型进化规划的异构神经网络集成算法.该算法首先利用改进的进化规划生成多个异构的最优网络,然后对异构网络进行组合求解.仿真实验表明,文中算法能够克服传统集成算法中成员网络结构固定、缺乏个体精度的缺点,具有比传统集成算法更好的泛化性能和更少的随机不确定因素.

关键词: 进化规划, 神经网络集成, 异构神经网络, Bootstrap采样, 泛化性能

Abstract:

In order to improve the generalization ability of ensemble algorithms and the objectivity of the generating process of individual networks, an algorithm of heterogeneous neural network ensemble is proposed based on a new evolutionary programming. In this algorithm, several heterogeneous optimal neural networks are generated based on an improved evolutionary programming and are further integrated to obtain a solution. Simulated results indicate that, as compared with the traditional ensemble algorithms with fixed network structure and low individual precision, the proposed algorithm is of stronger generalization ability and fewer random elements.

Key words: evolutionary programming, neural network ensemble, heterogeneous neural network, Bootstrap sampling, generalization ability