期刊文献+

一种改进的GEP神经网络演化方法及其应用 被引量:1

An Improved Method for Evolving GEP Neural Network
下载PDF
导出
摘要 标准GEP方法作为一种新型的演化计算方法在回归和分类方面已经取得了很好的效果。本文在简要介绍采用GEP演化神经网络的基础上,指出了该方法在二次及以上建模问题中所存在的缺陷,提出并实现了一种改进的GEP神经网络演化方法(IGEPNN),并将其应用到回归和分类问题中。实验证明该方法在回归和分类问题中具有良好的学习效果。
出处 《计算机系统应用》 2009年第4期49-52,共4页 Computer Systems & Applications
基金 国家自然科学基金项目(60673063) 国家863计划项目(2007AA12Z141) 浙江省自然科学基金项目(Y107551) 浙江省教育厅项目(20060815)
  • 相关文献

参考文献6

  • 1Ferreira C. Gene expression programming: a new adaptive algorithm for solving problems. Complex Systems, 2001,13(2):87- 129.
  • 2彭京,唐常杰,李川,胡建军.M-GEP:基于多层染色体基因表达式编程的遗传进化算法[J].计算机学报,2005,28(9):1459-1466. 被引量:32
  • 3Chi Z, Xiao WM, Tirpak TM, Nelson PC. Evolving accurate and compact classification rules with gene expression programming. IEEE Transactions on Evolutionary Computation, 2003,2(6):519 - 531.
  • 4Ferreira C. Designing Neural Networks Using Gene Expression Programming. The 9th Online World Conference on Soft Computing in Industrial Applications, 2004.
  • 5Witten IH, Frank E. Data Mining: Practical machine learning tools and techniques. 2nd Edition, Morgan Kaufinann, San Francisco, 2005.
  • 6Murphy PM, Aha DW. UCI Repository of Machine Learning Database. http://archive.ics.uci.edu/ml/datase -ts.html.

二级参考文献11

  • 1彭京,唐常杰,李川,陈安龙,胡建军.一种基于UD-Tree的分布式数据库新型复制架构[J].小型微型计算机系统,2004,25(12):2065-2069. 被引量:5
  • 2彭京,唐常杰,胡建军,陈安龙,李川.DIRM:基于动态信息路由的数据检索模型[J].四川大学学报(工程科学版),2005,37(1):108-115. 被引量:9
  • 3Ferreira C.. Discovery of the Boolean functions to the best density-classification rules using gene expression programming. In:Lutton E. et al. eds.. Proceedings of the 4th European Conference on Genetic Programming. Lecture Notes in Computer Science 2278. Berlin: Springer-Verlag, 2002, 51~60.
  • 4Ferreira C.. Analyzing the founder effect in simulated evolutionary processes using gene expression programming. In: Abraham A., Ruiz-del-Solar J., Kpen M. eds.. Soft Computing Systems: Design, Management and Applications. Netherlands: IOS Press, 2002,153~162.
  • 5Ferreira C.. Function finding and the creation of numerical constants in gene expression programming. In: Benitez J.M. et al. eds.. Advances in Soft Computing: Engineering Design and Maufacturing. Springer-Verlag, 2003, 257~266.
  • 6Zuo Jie, Tang Chang-Jie, Zhang Tian-Qing. Mining predicate association rule by gene expression programming. In: Meng Xiao-Feng, Su Jian-Wen, Wang Yu-Jun eds.. Proceedings of the International Conference for Web Information Age 2002. Lecture Notes in Computer Science 2419. Berling Heidelberg: Springer-Verlag, 2002, 92~103.
  • 7De Garis H. Evolvable hardware: The genetic programming of Darwin machines. In: Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, Innsbruck, Austria, 1993, 441~449.
  • 8Ferreira C.. Gene expression programming: A new adaptive algorithm for solving problems. Complex Systems, 2001, 13 (2): 87~129.
  • 9Ferreira C.. Gene Expression Programming.First Edition. Portugal: Angra do Heroismo, 2002.
  • 10Ferreira C.. Gene expression programming in problem solving. In: Proceedings of the 6th Online World Conference on Soft Computing in Industrial Applications, 2001, 635~654.

共引文献31

同被引文献8

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部