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Using stochastic dynamic step length particle swarm optimization to direct orbits of chaotic systems

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2 Author(s)
Xingjuan Cai ; Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China ; Zhihua Cui

Stochastic dynamic step length particle swarm optimization (SDSLPSO) is a new novel variant of particle swarm optimization that incorporating the dynamic step length for each particle in each iteration. This strategy simulates the phenomenon that each bird adjusts its velocity automatically in the process to finding the prey. In this paper, SD-SLPSO is employed to solve the directing orbits of chaotic systems, simulation results show this new variant increases the performance significantly when compared with the standard version of particle swarm optimization.

Published in:

Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on

Date of Conference:

7-9 July 2010