Alpha-cut representation of fuzzy sets has been used as a basis for fuzzy numbers ranking
in some applications but rarely used for defuzzification of rule-based systems or fuzzy …

This paper presents a toolkit for automatic generation and analysis of fuzzy sets (FS) from
data. Toolkits are vital for the wider dissemination, accessibility and implementation of …

Artificial neural network (ANN) inherently cannot explain in a comprehensible form how a
given decision or output is generated, which limits its extensive use. Fuzzy rules are an …

This paper proposes a cross-domain statistical method for comparing defuzzification
algorithms based on incorporating the concepts of fuzzy sets' pairwise operators of …

Similarity measures are useful for reasoning about fuzzy sets. Hence, many classical set-
theoretic similarity measures have been extended for comparing fuzzy sets. In previous …

Fuzzy sets (FSs) may have complex, non-normal, or non-convex membership functions that
occur, for example, in the output of a fuzzy logic system or when automatically generating …

Effectively measuring the similarity or dissimilarity of two vague concepts plays a key step in
reasoning and computing with vague concepts. In this paper, we define semantic distances …

Reasoning with fuzzy sets can be achieved through measures such as similarity and
distance. However, these measures can often give misleading results when considered …

Online big data provides large amounts of decision information to decision makers, but
supporting and opposing information are present simultaneously. Dual hesitant fuzzy sets …

The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set
theory, however, distance measures currently within the literature use a crisp value to …