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Jiaqiang E,ChunhuaWANG,YaonanWANG,Jinke GONG.[en_title][J].Control Theory and Technology,2008,6(2):141~145.[Copy]
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JiaqiangE,ChunhuaWANG,YaonanWANG,JinkeGONG
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Received:April 25, 2006Revised:May 24, 2007
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A new adaptive mutative scale chaos optimization algorithm and its application
Jiaqiang E, ChunhuaWANG, YaonanWANG, Jinke GONG
(College of Mechanical and Automotive Engineering, Hunan University, Changsha Hunan 410082, China; College of Electrical and Informational Engineering, Hunan University, Changsha Hunan 410082, China)
Abstract:
Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin(2/x) with infinite collapses within the finite region[-1;1] to some representative iterative chaotic maps with finite collapses (e.g., Logistic map, Tent map, and Chebyshev map), a new adaptive mutative scale chaos optimization algorithm (AMSCOA) is proposed by using the chaos model x = in(2/x). In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken: 1) the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2) the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.
Key words:  Adaptive  Mutative scale  Chaos optimization algorithm  One-dimensional iterative chaotic self-map