@article{Ashraf2023, 
author = {Shahzaib Ashraf and Huzaira Razzaque and Muhammad Naeem and Thongchai Botmart},
title = {Spherical q-linear Diophantine fuzzy aggregation information: Application in decision support systems},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {3},
pages = {6651-6681},
keywords = {decision making, aggregation operators, spherical q-linear Diophantine fuzzy set, operational laws},
url = {https://www.sciopen.com/article/10.3934/math.2023337},
doi = {10.3934/math.2023337},
abstract = {The main goal of this article is to reveal a new generalized version of the q-linear Diophantine fuzzy set (q-LDFS) named spherical q-linear Diophantine fuzzy set (Sq-LDFS). The existing concepts of intuitionistic fuzzy set (IFS), q-rung orthopair fuzzy set (q-OFS), linear Diophantine fuzzy set (LDFS), and spherical fuzzy set have a wide range of applications in decision-making problems, but they all have strict limitations in terms of membership degree, non-membership degree, and uncertainty degree. We moot the article of the spherical q-linear Diophantine fuzzy set (Sq-LDFS) with control factors to alleviate these limitations. A Spherical q-linear Diophantine fuzzy number structure is independent of the selection of the membership grades because of its control parameters in three membership grades. An Sq-LDFS with a parameter estimation process can be extremely useful for modeling uncertainty in decision-making (DM). By using control factors, Sq-LDFS may classify a physical system. We highlight some of the downsides of q-LDFSs. By using algebraic norms, we offer some novel operational laws for Sq-LDFSs. We also introduced the weighted average and weighted geometric aggregation operators and their fundamental laws and properties. Furthermore, we proposed the algorithms for a multicriteria decision-making approach with graphical representation. Moreover, a numerical illustration of using the proposed methodology for Sq-LDF data for emergency decision-making is presented. Finally, a comparative analysis is presented to examine the efficacy of our proposed approach.}
}