The goal of this work is to study, expand and evaluate the use of multiobjective genetic algorithms and the iterative rule learning approach in fuzzy system generation, especially, in fuzzy rule-based systems, both in ...

The construction of the knowledge base of fuzzy systems has been beneficited intensively from automatic methods that extract the necessary knowledge from data sets which represent examples of the problem. The evolutionary ...

The objective of this work is to study, expand and evaluate the use of interval type-2 fuzzy sets in the knowledge representation for fuzzy inference systems, specifically for fuzzy classifiers, as well as its automatic ...

The process of building the knowledge base of fuzzy systems has benefited extensively of methods to automatically extract the necessary knowledge from data sets that represent examples of the problem. Among the topics ...

This work focuses on the problem of automatic generation of fuzzy systems through evolutionary computation, specifically using the approach of co-evolution. Coevolution is based on the idea of modular modeling of the ...

The automatic generation and optimization of Fuzzy Systems is an important area because the manually generation and optimization is very hard and may require one or more specialists. Even with the help of specialists the ...

On this paper, it is made a comparative analysis among a controller fuzzy coupled to a PID neural adjusted by an AGwith several traditional control techniques, all of them applied in a system of tanks (I model of 2nd ...