Chaotic System Parameter Identification Based on Firefly Optimization

Abstract:

Firefly Optimization Algorithm (FA) is a novel heuristic stochastic algorithm based on swarm intelligence, which is inspired by the fireflies biochemical and collective behavior. Due to the increment of attractiveness and the fixed step factor, the optimizing results are easily repeated oscillation on the position of local or global extreme value point, and the optimizing accuracy is reduced. Accordingly, this paper puts forward chaos firefly optimization algorithm (CFA), the improved algorithm can improve the diversity of population and the ergodicity of optimization, increase the ability of getting rid of trapped into local minima point. Chaos firefly optimization algorithm is used for the identification of chaotic system parameter; the results show the high accuracy of the algorithm parameter identification.

• Periodical: Applied Mechanics and Materials (Volumes 347-350)
• Pages: 3821-3826
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.347-350.3821
• Online since: August 2013
• Authors: Wei Ming Gao, Zhi Cheng Zhang, Yao Hua Chong
• Keywords: Firefly Algorithm, Inertia Weight, Parameters Identification, Swarm Intelligence

References

[1] YANG Xin-she．Nature-inspired metaheuristic algorithms [M]．[s. 1. ]: Luniver Press, (2008).

[2] Ming-Huwi Horng. Vector quantization using the firefly algorithm for image compression[J]. Expert Systems with Applications, 2012, 1078-1091.

DOI: 10.1016/j.eswa.2011.07.108

[3] A. Chatterjee G.K. Mahanti, and Arindam Chatterjee. Design of a fully digital controlled reconfigurable switched beam concentric ring array antenna using firefly and particle swarm optimization algorithm[J]. Progress In Electromagnetics Research B, 2012, 36: 113-131.

DOI: 10.2528/pierb11083005

[4] Amir Hossein Gandomi, Xin-She Yang, Amir Hossein Alavi. Mixed variable structural optimization using Firefly Algorithm[J]. Computers and Structures, 2011, 89: 2325-2336.

DOI: 10.1016/j.compstruc.2011.08.002

[5] Ming-Huwi Horng , Ren-Jean Liou. Multilevel minimum cross entropy threshold selection based on the firefly algorithm[J]. Expert Systems with Applications, 2011, 38: 14805-14811.

DOI: 10.1016/j.eswa.2011.05.069

[6] Gilang Kusuma Jati and Suyanto. Evolutionary discrete firefly algorithm for travelling salesman problem[M]. ICAIS2011, Lecture Notes in Artificial Intelligence (LNAI 6943), (2011).

DOI: 10.1007/978-3-642-23857-4_38

[7] Theofanis Apostolopoulos, Aristidis Vlachos. Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem[A]. Hajo Broersma. International Journal of Combinatorics 2011[C]: Article ID 523806.

DOI: 10.1155/2011/523806

[8] B. Rampriya, K. Mahadevan, S. Kannan. Unit commitment in deregulated power system using Lagrangian firefly algorithm[A]. Proc. of IEEE Int. Conf. on Communication Control and Computing Technologies (ICCCCT), pp.389-393.

DOI: 10.1109/icccct.2010.5670583

[9] Wang lin, Liu bo. Particle swarm optimization and scheduling algorithm [M] Beijing: tsinghua university press, (2008).

[10] Ji zhen, Liao huilian, Wu qinghua. Particle swarm optimization (pso) algorithm and application [M]. Beijing: China science press, (2009).

[11] Lorenz, E. N., Deterministic nonperiodic flow, J. Atmos. Sci., 20, 130-141, (1963).

[12] Li lixiang, Pen haipeng, Yang yixian. Based on chaos ant group algorithm Lorenz chaos system parameter estimation [J]. Physics journal, 2007 , 56 : 51-55.