Particle swarm optimizer (PSO) is an intelligent algorithm which simulates the hunting activity of the group of birds. It's very clear, easy-defined, simple-operation and realizable. It can be used in radar-network to solve the program of radar system error. However, PSO is one of probability optimizer with premature phenomenon which makes it impossible for PSO to be guaranteed the global optimization solution to converge. The solutions used now have much shortage, so MV/spl I.bar/PSO is introduced with concept of multi-velocity and speed coefficient. Its application to radar-network proves that MV/spl I.bar/PSO is useful. Compared with standard PSO, MV/spl I.bar/PSO has better global optimal capability with faster evolution speed and higher accuracy. Compared with traditional Gauss-Newton, MV/spl I.bar/PSO is clearer and simpler to use.


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    Titel :

    A new particle swarm optimizer algorithm and application


    Beteiligte:
    Bo Wang, (Autor:in) / Yunlong Dong, (Autor:in) / CanLin Wang, (Autor:in) / QinLin Qu, (Autor:in)


    Erscheinungsdatum :

    01.01.2006


    Format / Umfang :

    3289607 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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