COMPARISON OF FUZZY SYSTEM WITH NEURAL AGGREGATION FSNA WITH CLASSICAL TSK FUZZY SYSTEM IN ANTI-COLLISION PROBLEM OF USV
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.
Keywords:
neuro-fuzzy system, neural aggregation of fuzzy rules, cooperative co-evolution, anti-collision of USVDetails
- Issue
- Vol. 24 No. 3(95) (2017)
- Section
- Latest Articles
- Published
- 11-10-2017
- DOI:
- https://doi.org/10.1515/pomr-2017-0085
- Licencja:
-
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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