Automatic synthesis of fuzzy systems: An evolutionary overview with a genetic programming perspective
Author:
Affiliation:
1. Department of Computer Science University College London (UCL) London UK
2. Department of Electrical Engineering Pontifical Catholic University of Rio de Janeiro (PUC‐Rio) Rio de Janeiro Brazil
Funder
Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Publisher
Wiley
Subject
General Computer Science
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1251
Reference116 articles.
1. Neuro fuzzy systems: State‐of‐the‐art modeling techniques;Abraham A.;Connectionist models of neurons, learning processes, and artificial intelligence. IWANN 2001. Lecture notes in computer science,2001
2. Alba E. Cotta C. &Troya J. M.(1996 July). Type‐constrained genetic programming for rule‐base definition in fuzzy logic controllers. InProceedings of the 1st annual conference on genetic programming(pp. 255–260). MIT Press.
3. A Fast and Scalable Multiobjective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems
4. Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions
5. Special Issue on Evolutionary Fuzzy Systems
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