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Proceedings Paper

Evolutionary algorithms for training neural networks
Author(s): Chilukuri K. Mohan
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Paper Abstract

This paper surveys the various approaches used to apply evolutionary algorithms to develop artificial neural networks that solve pattern recognition, classification, and other tasks. These approaches are classified into four groups, each addressing one aspect of an artificial neural network: (a) evolving connection weights; (b) evolving neural architectures; (c) evolving an ensemble of networks; and (d) evolving node functions. Hybrid approaches are also discussed.

Paper Details

Date Published: 20 May 2006
PDF: 9 pages
Proc. SPIE 6228, Modeling and Simulation for Military Applications, 62280Q (20 May 2006); doi: 10.1117/12.670263
Show Author Affiliations
Chilukuri K. Mohan, Syracuse Univ. (United States)

Published in SPIE Proceedings Vol. 6228:
Modeling and Simulation for Military Applications
Kevin Schum; Alex F. Sisti, Editor(s)

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