In contrast to two-way decisions (2WD), three-way decisions (3WD) can effectively reduce
decision risks by utilizing a new delayed decision option. This article incorporates 3WD into …

Three-way decisions provide a new research perspective for solving decision-making
problems. Under a multiple-criteria environment, this paper proposes a novel decision …

Clustering is a significant unsupervised learning method in the machine learning field, which
can mine the distribution pattern and attribute of data. However, traditional clustering …

Multi-attribute group decision making (MAGDM) is a common activity for multi-variable
complicated decision making situations by integrating collective wisdom. Aiming at fusing …

In real world, multi-attribute group decision making (MAGDM) is a complicated cognitive
process that involves expression, fusion and analysis of multi-source uncertain information …

As an important expanded quantification fuzzy rough set model, the local fuzzy rough set
model is used to measure relative quantitative information between the fuzzy similarity …

In this paper, we propose the concepts of hesitant bipolar-valued fuzzy sets (HBVFSs) and
bipolar-valued hesitant fuzzy sets (BVHFSs). The HBVFSs encompass bipolar-valued fuzzy …

In this paper, we study interval-valued fuzzy probabilistic rough sets (IVF-PRSs) based on
multiple interval-valued fuzzy preference relations (IVFPRs) and consistency matrices, ie …

Aiming at the problems of filling missing information and calculating conditional probability
and loss function in incomplete information systems, this paper provides a novel three-way …

The multigranulation rough set model is a critical issue in rough set theory, where target
concepts are approximated based on multiple binary relations on the universe. In this work …