Research Article

Cooperating swarms: A paradigm for collective intelligence and its application in finance

by  Sumona Mukhopadhyay, Santo Banerjee
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Issue 10
Published: September 2010
Authors: Sumona Mukhopadhyay, Santo Banerjee
10.5120/1107-1450
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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
Abstract

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.

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Computational intelligence particle swarm optimization Finance system chaos multi-objective global optimization

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