Uncertainty and imprecision accompany the world we live in and occur in almost every
event. How to better interpret and manage uncertainty and imprecision play a vital role in …

Multi-view clustering has attracted substantial attention thanks to its ability to integrate
information from diverse views. However, the existing methods can only generate hard or …

Fermatean fuzzy sets (FFSs) have emerged as a powerful tool for handling uncertain
information and have been successfully applied in various domains. However, the existing …

The applications of clustering in biomedical is pervasive and ubiquitous. A typical example
is gene expression data analysis, where clustering is emerging as a powerful solution for …

Clustering incomplete instance is still a challenging task since missing values maybe make
the cluster information ambiguous, leading to the uncertainty and imprecision in results. This …

It remains challenging in characterizing uncertain and imprecise information when clustering
fuzzy number data. To solve such a problem, this paper investigates a new credal-based …

Dempster-Shafer theory (DST) has attracted wide attention in many fields thanks to its strong
advantages over probability theory. Whereas the uncertainty measure of basic belief …

Data clustering has emerged as a prospective technique for analyzing interval-valued data
and has found extensive applications across various practical domains. However, the …

It remains challenging in managing uncertain and imprecise information in multisensor data
fusion. Dempster–Shafer evidence theory (DSET), which has a strong appeal for modeling …

Picture fuzzy sets (PFSs), as a generalization of traditional fuzzy sets and intuitionistic fuzzy
sets (IFSs), offer a powerful framework for modeling and dealing with imprecise and …