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 concept of intuitionistic fuzzy set (IFS) has extensively used to handle the uncertainty of
real-life decision making problems. The aim of this study is to propose an integrated …

Cluster analysis is a crucial issue in multivariate statistics and data science due to its
application in various fields. This study proposes a cutting-edge clustering algorithm for …

Fuzzy similarity measures are utilized to match two or more records and are essential to deal
with data classification and pattern-matching problems. We have noticed that the existing …

Now-a-days, due to the increasing demand of the energy resources across the world,
choosing the best sustainable biomass crop for the production of biofuels is a strategic …

In the modern era, transportation has also become more expensive due to fluctuations in the
prices of fuels and gasses. We demonstrate an efficient transportation system to cope with …

In the era of complex data, clustering techniques are useful in data mining. However, there
are tremendous numbers of clustering techniques available in literature. Out of them, Fuzzy …

Atanassov intuitionistic fuzzy sets (AIFSs) are substantially more effective at capturing and
processing uncertainty than fuzzy sets. More focus has been placed on the knowledge …

As an extension of q-rung orthopair fuzzy set, interval-valued q-rung orthopair fuzzy set (IVq-
ROFS) provides a more wider decision interval to express the fuzziness information. This …

This paper introduces a novel multiattribute group decision making (MAGDM) method under
the linguistic q-rung orthopair fuzzy (Lq-ROF) environment based on the proposed Lq-ROF …