Comparison of fuzzy system with neural aggregation FSNA with classical TSK fuzzy system in anti-collision problem of USV

• Autorzy: Symak P.
• Języki publikacji: EN

Abstrakty

EN

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

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2017
• Tom: 24
• Numer: 3
• Opis fizyczny: p.3-14,fig.,ref.

Twórcy

autor

Symak P.

• Polish Naval Academy, Smidowicza 69, 81-127 Gdynia, Poland

Bibliografia

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Identyfikatory

DOI

10.1515/pomr-2017-0085