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 …

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 …

As a core paradigm of the evidential clustering algorithm, evidential c-means (ECM) offers a
more flexible credal partition to characterize uncertainty and imprecision in cluster …

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 …

Abstract Complex Fermatean fuzzy sets (CFFSs) integrate the ideas of complex fuzzy sets
and Fermatean fuzzy sets, where the membership, non-membership, and hesitancy degrees …

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 …

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 …

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 …

How to effectively deal with uncertain and imprecise information in decision making is a
complex task. Dempster-Shafer evidence theory (DSET) is widely used for handling such …

Currently, many studies have developed distance or divergence measures between
intuitionistic fuzzy sets (IFSs) and interval-valued fuzzy sets (IvFSs). As a generalization of …