Linguistic fuzzy modelling, developed by linguistic fuzzy rule-based systems, allows us to
deal with the modelling of systems by building a linguistic model which could become …

In this paper, a multiobjective genetic fuzzy system (GFS) to learn the granularities of fuzzy
partitions, tuning the membership functions (MFs), and learning the fuzzy rules is presented …

This paper discusses the relevance and possible applications of evolutionary algorithms,
particularly genetic algorithms, in the domain of knowledge discovery in databases …

Finding the best classifiers according to different criteria is often performed by a multi-
objective machine learning algorithm. This study considers two criteria that are usually …

\Living organism are consummate problem solvers. They exhibit a versatility that puts the
best computer programs to shame." John H. Holland 1] The material of this bibliography has …

An Indexed Bibliography of Genetic Algorithms with Fuzzy Systems Page 1 An Indexed
Bibliography of Genetic Algorithms with Fuzzy Systems compiled by Jarmo T. Alander …

We propose a multi-objective machine learning approach guaranteed to find the Pareto
optimal set of hybrid classification models consisting of comprehensible and …

An Indexed Bibliography of Genetic Algorithms in Machine Learning Page 1 An Indexed
Bibliography of Genetic Algorithms in Machine Learning compiled by Jarmo T. Alander …

An Indexed Bibliography of Genetic Algorithms in the Nordic and Baltic Countries Page 1 An
Indexed Bibliography of Genetic Algorithms in the Nordic and Baltic Countries compiled by …

In this paper, we propose the accommodation of the semantic-based interpretability in
evolutionary linguistic fuzzy controller through an overlap-based encoding strategy for the …