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    Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation

    Access Status
    Fulltext not available
    Authors
    Ling, S.
    Nguye, H.
    Leung, F.
    Chan, Kit Yan
    Jiang, F.
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Ling, Sai Ho and Nguyen, Hung and Leung, Frank and Chan, Kit Yan and Jiang, Frank. 2012. Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation, in IEEE Congress on Evolutionary Computation, Jun 10-15 2012, pp. 3009-3016. Brisbane, Qld: IEEE.
    Source Title
    Proceedings of the IEEE Congress on Evolutionary Computation
    Source Conference
    IEEE Congress on Evolutionary Computation
    DOI
    10.1109/CEC.2012.6252934
    ISBN
    978-1-4673-1508-1
    URI
    http://hdl.handle.net/20.500.11937/35908
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM), where a fuzzy logic is applied to determine the inertia weight of PSO and the control parameter of the proposed cross-mutated operation based on human knowledge. By introducing the fuzzy system, the value of the inertia weight of PSO becomes adaptive. The new cross-mutated operation effectively drives the solution to escape from local optima. To illustrate the performance of the FPSOCM, a suite of benchmark test functions are employed. Experimental results show the proposed FPSOCM method performs better than some existing hybrid PSO methods in terms of solution quality and solution reliability (standard deviation upon many trials).Moreover, an industrial application of economic load dispatch is given to show that the FPSOCM method performs statistically more significant than the existing hybrid PSO methods.

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