In recent years, a great number of publications have explored the use of genetic algorithms
as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this …

Fuzzy Systems have shown their utility for solving a wide range of problems in different
application domains. The use of Genetic Algorithms for designing Fuzzy Systems allows us …

Although fuzzy systems demonstrated their ability to solve different kinds of problems in
various applications, there is an increasing interest on augmenting them with learning …

The use of genetic algorithms for designing fuzzy systems provides them with the learning
and adaptation capabilities and is called genetic fuzzy systems (GFSs). This topic has …

Ever since fuzzy logic was introduced by Lotfi Zadeh in the mid-sixties and genetic
algorithms by John Holland in the early seventies, these two fields widely been subjects of …

This paper considers the application of a genetics-based learning algorithm to systems
based on fuzzy logic. One of the more active areas in the application of fuzzy logic is fuzzy …

Soft Computing is concerned with modes of computing in which precision is treated for
tractability, robustness and ease of implementation, and it contains Fuzzy Sets and Genetic …

Abstract Evolutionary Fuzzy Systems are a successful hybridization between fuzzy systems
and Evolutionary Algorithms. They integrate both the management of imprecision …

Genetic algorithms (GAs) represent a class of adaptive search techniques inspired by
natural evolution mechanisms. The search properties of GAs make them suitable to be used …

Genetic fuzzy systems (GFS) are based on the use of genetic algorithms for designing fuzzy
systems, and for providing them with learning and adaptation capabilities. In this context …