International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 6 - Issue 10 |
Published: September 2010 |
Authors: Sumona Mukhopadhyay, Santo Banerjee |
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Sumona Mukhopadhyay, Santo Banerjee . Cooperating swarms: A paradigm for collective intelligence and its application in finance. International Journal of Computer Applications. 6, 10 (September 2010), 31-41. DOI=10.5120/1107-1450
@article{ 10.5120/1107-1450, author = { Sumona Mukhopadhyay,Santo Banerjee }, title = { Cooperating swarms: A paradigm for collective intelligence and its application in finance }, journal = { International Journal of Computer Applications }, year = { 2010 }, volume = { 6 }, number = { 10 }, pages = { 31-41 }, doi = { 10.5120/1107-1450 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2010 %A Sumona Mukhopadhyay %A Santo Banerjee %T Cooperating swarms: A paradigm for collective intelligence and its application in finance%T %J International Journal of Computer Applications %V 6 %N 10 %P 31-41 %R 10.5120/1107-1450 %I Foundation of Computer Science (FCS), NY, USA
The control of nonlinear chaotic system and the estimation of parameters is a vital issue in nonlinear science. Studies on parameter estimation for chaotic systems have been investigated recently. A variant of Particle Swarm Optimization (PSO) known as Chaotic Multi Swarm Particle Swarm Optimization (CMS-PSO) is proposed which is inspired from the metaphor of ecological co-habitation of species. The generic PSO is modified with the chaotic sequences for multi-dimension parameter estimation and optimization by forming multiple cooperating swarms. Results demonstrate the effectiveness of the scheme in successfully estimating the unknown parameters of a new hyperchaotic finance system. Numerical results and comparison demonstrate that for the given parameters of the nonlinear system, CMS-PSO can identify the optimized parameters effectively to reach the pareto optimal solution and convergence speed.