Fuzzy sets emerged in 1965 in a paper by Lotfi Zadeh. In 1969 Ruspini published a seminal
paper that has become the basis of most fuzzy clustering algorithms. His ideas established …

Since its inception in 1965, the theory of fuzzy sets has advanced in a variety of ways and in
many disciplines. Applications of this theory can be found, for example, in artificial …

The notion of uncertainty is of major importance in machine learning and constitutes a key
element of machine learning methodology. In line with the statistical tradition, uncertainty …

This paper describes the new intuitionistic fuzzy aggregation operators in consequence of
Aczel–Alsina operations that possess certain advantages in cases of solving real life …

The aggregation of fuzzy information is a new area of “intuitionistic fuzzy set (IFS)” theory
that has piqued the attention of scholars in the past few years. This study aims to construct …

Abstract q-rung orthopair fuzzy sets (q-ROFSs) are advantageous for accurately expressing
the preferences of decision-makers (DMs) due to their membership and non-membership …

Attempts at combining logic and neural networks into neurosymbolic approaches have been
on the increase in recent years. In a neurosymbolic system, symbolic knowledge assists …

Traffic congestion and environmental pollution generated by transportation activities
significantly endanger the sustainable development of cities. This study presents a new …

Reasonable and effective assessment of express service quality can help express company
discover its own shortcomings and overcome them, which is crucial significant to enhance its …

Nowadays, with the increasing complexity of decision-making environment, more and more
large-scale group decision making (LGDM) problems are faced. Due to the existence of …