• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations | Disambiguate

DMCA

Evolving Artificial Neural Networks (1999)

Cached

  • Download as a PDF

Download Links

  • [www.cs.bham.ac.uk]
  • [www.cs.bham.ac.uk]
  • [sci2s.ugr.es]
  • [candy.yonsei.ac.kr]
  • [www.cs.bham.ac.uk]
  • [www.macs.hw.ac.uk]
  • [sclab.yonsei.ac.kr]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Xin Yao
Citations:573 - 6 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Yao99evolvingartificial,
    author = {Xin Yao},
    title = {Evolving Artificial Neural Networks},
    year = {1999}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

This paper: 1) reviews different combinations between ANN's and evolutionary algorithms (EA's), including using EA's to evolve ANN connection weights, architectures, learning rules, and input features; 2) discusses different search operators which have been used in various EA's; and 3) points out possible future research directions. It is shown, through a considerably large literature review, that combinations between ANN's and EA's can lead to significantly better intelligent systems than relying on ANN's or EA's alone

Keyphrases

artificial neural network    various ea    different combination    ann connection weight    intelligent system    input feature    discus different search operator    evolutionary algorithm    possible future research direction    large literature review   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University