Back to Search
Start Over
Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm.
- Source :
-
Physics Letters A . Mar2016, Vol. 380 Issue 11/12, p1164-1171. 8p. - Publication Year :
- 2016
-
Abstract
- A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03759601
- Volume :
- 380
- Issue :
- 11/12
- Database :
- Academic Search Index
- Journal :
- Physics Letters A
- Publication Type :
- Academic Journal
- Accession number :
- 112848494
- Full Text :
- https://doi.org/10.1016/j.physleta.2016.01.040