Evolutionary algorithms for training neural networks

Chilukuri K. Mohan

doi:10.1117/12.670263

20 May 2006 Evolutionary algorithms for training neural networks

Chilukuri K. Mohan

Proceedings Volume 6228, Modeling and Simulation for Military Applications; 62280Q (2006) https://doi.org/10.1117/12.670263
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

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.

Citation Download Citation

Chilukuri K. Mohan "Evolutionary algorithms for training neural networks", Proc. SPIE 6228, Modeling and Simulation for Military Applications, 62280Q (20 May 2006); https://doi.org/10.1117/12.670263

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