title: Parameter estimation of dynamical systems via a chaotic ant swarm.
abstract: Through the construction of suitable objective function, the parameter estimation of the dynamical system could be converted to the problem of parameter optimization. Based on the chaotic ant swarm optimization approach, we investigate the problem of parameter optimization for the dynamical systems in the presence of noise. We systematically analyze the basic relationships among the complexity of objective function, the length of time series, and the performance of the searching algorithm. Furthermore, we consider the effect of measurable additive noise on the objective function. Numerical simulations are also provided to show the effectiveness and feasibility of the proposed methods.
authors.affiliation: Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China.
authors.forename: Haipeng
authors.initials: H
authors.lastname: Peng
authors.forename: Lixiang
authors.initials: L
authors.lastname: Li
authors.forename: Yixian
authors.initials: Y
authors.lastname: Yang
authors.forename: Fei
authors.initials: F
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D000818:Animals; D001000:Ants; D001522:Behavior, Animal; D003198:Computer Simulation; D005240:Feasibility Studies; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D013997:Time Factors