Improved Artificial Fish Swarm Algorithm and its Application in System Identification

DOI

10.2991/emeit.2012.442How to use a DOI?

Keywords

Artificial Fish Swarm AlgorithmNeedle-in-haystack Problem Parameter Identification

Abstract

In order to solve the traditional identification method limitations, This paper presents an improved artificial fish swarm algorithm, Through the experiment of a typical Needle-in-haystack problem, Show that the improved artificial fish swarm algorithm has better ability of global optimization, faster convergence speed, higher accuracy of optimization. This algorithm is applied to the system parameter identification , Through to the linear system and nonlinear system parameter identification simulation, Results show that the algorithm has fast convergence, high accuracy advantages, Has important application value in Engineering.

Copyright

© 2012, 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  - Junlin Zhu
AU  - Hui Liu
AU  - Zulin Wang
PY  - 2012/09
DA  - 2012/09
TI  - Improved Artificial Fish Swarm Algorithm and its Application in System Identification
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 1994
EP  - 1997
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.442
DO  - 10.2991/emeit.2012.442
ID  - Zhu2012/09
ER  -