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 sets were first proposed by Lotfi Zadeh in his seminal paper [366] in 1965, and ever
since have been a center of many discussions, fervently admired and condemned. Both …

Fuzzy rule-based systems (FRBSs) are a well-known method family within soft computing.
They are based on fuzzy concepts to address complex real-world problems. We present the …

Fuzzy Rule-Based Systems have been succesfully applied to pattern classification
problems. In this type of classification systems, the classical Fuzzy Reasoning Method (FRM) …

Learning and recognizing human activities of daily living (ADL), is very useful and essential
to build a pervasive home monitoring system. These monitoring technologies are …

Fingerprint classification is an important indexing method for any large scale fingerprint
recognition system or database as a method for reducing the number of fingerprints that …

The inductive learning of a fuzzy rule-based classification system (FRBCS) is made difficult
by the presence of a large number of features that increases the dimensionality of the …

A new algorithm, namely Z− numbers-based deep feature thresholding (Z− DFT) is
described for handling the issue concerning uncertainty that arises while classifying various …

In this paper, we present a multistage genetic learning process for obtaining linguistic fuzzy
rule-based classification systems that integrates fuzzy reasoning methods cooperating with …

A method is proposed for finding decision boundaries, approximated by piecewise linear
segments, for the classification of patterns in R 2 using an elitist model of a genetic …