Review of efforts combining neural networks and evolutionary computation

David B. Fogel; Peter J. Angeline

doi:10.1117/12.205162

6 April 1995 Review of efforts combining neural networks and evolutionary computation

David B. Fogel, Peter J. Angeline

Proceedings Volume 2492, Applications and Science of Artificial Neural Networks; (1995) https://doi.org/10.1117/12.205162
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Since the widespread recognition of the capacity for neural networks to perform general function approximation, a variety of such mapping functions have been used to address difficult problems in pattern recognition, time series forecasting, automatic control, image compression, and other engineering applications. Although these efforts have met with considerable success, the design and training of neural networks have remained much of an art, relying on human expertise, trial, and error. More recently, methods in evolutionary computation, including genetic algorithms, evolution strategies, and evolutionary programming, have been used to assist in and automate the design and training of neural networks. This presentation offers a review of these efforts and discusses the potential benefits and limitations of such combinations.

Citation Download Citation

David B. Fogel and Peter J. Angeline "Review of efforts combining neural networks and evolutionary computation", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); https://doi.org/10.1117/12.205162

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available