Extreme learning machine based on improved genetic algorithm

DOI

10.2991/icimm-15.2015.38How to use a DOI?

Keywords

Improvedgeneticalgorithm;Extreme learning machine; Function approximation

Abstract

This paper puts forward a novel algorithm called extreme learning machine (ELM)which is optimized by improved genetic algorithm(IGA), and points out the weaknesses of ELM. The input weights and thresholds randomly generated by ELM are optimized by IGA. After it, ELM can get the more effective input weights and thresholds and be better applied in function approximation. The results of simulation shows that the optimized algorithm has a high approximation accuracy and faster convergence speed.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hai Liu
AU  - Bin Jiao
AU  - Long Peng
AU  - Ting Zhang
PY  - 2015/07
DA  - 2015/07
TI  - Extreme learning machine based on improved genetic algorithm
BT  - Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials
PB  - Atlantis Press
SP  - 199
EP  - 204
SN  - 2352-5401
UR  - https://doi.org/10.2991/icimm-15.2015.38
DO  - 10.2991/icimm-15.2015.38
ID  - Liu2015/07
ER  -