@inproceedings{435b4d6555fd4b74ae2dcc346b2048b1,
title = "Evolutionary algorithms for training neural networks",
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.",
keywords = "Ensemble models, Evolutionary algorithms, Model learning, Neural networks, Optimization, Parameter learning",
author = "Mohan, {Chilukuri K.}",
year = "2006",
doi = "10.1117/12.670263",
language = "English (US)",
isbn = "0819462845",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Modeling and Simulation for Military Applications",
note = "Modeling and Simulation for Military Applications ; Conference date: 18-04-2006 Through 21-04-2006",
}