
Parameter estimation for Lorenz chaotic systems based on chaotic ant swarm algorithm
Author(s) -
Lixiang Li,
Haipeng Peng,
Yixian Yang,
Xiangdong Wang
Publication year - 2007
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.56.51
Subject(s) - chaotic , swarm behaviour , lorenz system , computer science , swarm intelligence , ant colony optimization algorithms , algorithm , mathematical optimization , mathematics , particle swarm optimization , artificial intelligence
The chaotic ant swarm algorithm is a chaos optimization algorithm based on swarm intelligence theory which was inspired by the chaotic and self-organizing behavior of the ants in nature. It includes both effects of chaotic dynamics and swarm-based search. Through the construction of a suitable fitness function, the problem of parameter estimation of the chaotic system is converted to a problem of parameter optimization which could be solved via chaotic ant swarm algorithm. Chaotic ant swarm algorithm has the ability of global search. A numerical simulation on the well-known Lorenz chaotic system is conducted. Simulation results show that the proposed method is effective in parameter estimation of the chaotic system.