Abstract The paper presents the research whose the main goal was to compare a new Fuzzy System with Neural Aggregation of fuzzy rules FSNA with a classical Takagi-Sugeno-Kanga TSK fuzzy system in an anti-collision problem of Unmanned Surface Vehicle USV. Both systems the FSNA and the TSK were learned by means of Cooperative Co-evolutionary Genetic Algorithm with Indirect Neural Encoding CCGA-INE. The paper includes an introduction to the subject, a description of the new FSNA and the tuning method CCGA-INE, and at the end, numerical research results with a summary. The research includes comparison of the FSNA with the classical TSK system in the anti-collision problem of the USV.


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    Titel :

    Comparison of Fuzzy System with Neural Aggregation FSNA with Classical TSK Fuzzy System in Anti-Collision Problem of USV


    Beteiligte:
    Szymak, Piotr (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Unbekannt


    Klassifikation :

    BKL:    50.92 Meerestechnik / 55.40 Schiffstechnik, Schiffbau




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