To better handle real-world uncertainty, concepts such as fuzzy sets, neutrosophic sets,
rough sets, and soft sets have been introduced. For example, neutrosophic sets, which …

Concept-cognitive learning (CCL) and three-way decision (3WD) models provide powerful
techniques for knowledge discovery. Some early attempts in the field have successfully …

Uncertain Graph Theory has emerged to model the uncertainties present in real-world
networks. An Incidence Graph represents the connections between vertices and edges …

Graph theory, a branch of mathematics, studies the relationships between entities using
vertices and edges. Uncertain Graph Theory has emerged within this field to model the …

A basic task of Pawlak conflict analysis is to cluster agents based on their attitudes towards
various issues. When ratings of agents are imprecise and uncertain, for example, as …

Graph theory, a branch of mathematics, explores relationships among objects using vertices
and edges [106]. A specialized area within this field, Uncertain Graph Theory, is designed to …

The concept of bipolar-valued fuzzy set was introduced by Zhang. Can we discuss three-
way decisions based on bipolar-valued fuzzy sets over three-way decision spaces? In …

A bunch of stream clustering algorithms have been proposed recently to mine data streams
generated at high speeds from hardware platforms and software applications. Density …

Rough set theory is a well-known mathematical framework that can deal with inconsistent
data by providing lower and upper approximations of concepts. A prominent property of …

Evidence theory has been applied in structural reliability assessment to address epistemic
uncertainties, given its capability to deal with imprecise, incomplete and even contradictory …