A Novel Global Artificial Fish Swarm Algorithm with Improved Chaotic Search

Ying Xu; Hon Gan Chen

doi:10.4028/www.scientific.net/AMR.538-541.2594

Paper Titles

Blind Separation of Non-Stationary Convoluted Mixtures Based on Time-Frequency Analysis
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Free Vibration of Piezoelectric Laminated Cylindrical Shell with Delamination
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Stochastic Resonance in a Second-Order Linear System Subject to Signal-Modulated Noise
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Parallel Topology Optimization of Bi-Material Layout for Vibration Control in Plate Structures
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A Novel Global Artificial Fish Swarm Algorithm with Improved Chaotic Search
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Stochastic Resonance Enhanced by Colored Multiplicative and Additive Noises in a Time-Delayed Bistable System
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Gain Adjustable Intelligent Tracking Algorithm
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An Adaptive Tracking Algorithm Based on Mean Shift
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A Fast Algorithm for Workspace of a Robotic Manipulator
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 538-541A Novel Global Artificial Fish Swarm Algorithm...

A Novel Global Artificial Fish Swarm Algorithm with Improved Chaotic Search

Abstract:

The artificial fish swarm algorithm, it may be trapped in local optimum in the later evolution period and its search accuracy is dependent on step length which is hard to keep balance between rapidity and accuracy. Aimed at the defects of AFSA, a novel global artificial fish swarm algorithm is proposed in this paper, in which normal chaotic search on earlier stage is modified , and a differential evolution with improved chaos search was proposed to lead artificial fish into global optimum value. The experimental results show that the proposed algorithm is not only superior to traditional one but also can make the result greater.

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Periodical:

Advanced Materials Research (Volumes 538-541)

Pages:

2594-2597

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.538-541.2594

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Online since:

June 2012

Authors:

Ying Xu, Hon Gan Chen

Keywords:

Artificial Fish-Swarm Algorithm (AFSA), Chaotic Search, Differential Evolution, Global Optimum

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