Work

Novel Distance Measures of q-Rung Orthopair Fuzzy Sets and Their Applications

Year: 2024

Type: article

Abstract: The q-rung orthopair fuzzy sets (q-ROFSs), a novel concept for processing vague information, offer a more potent and all-encompassing method compared to traditional fuzzy sets, intuitionistic fuzzy sets, and Pythagorean fuzzy sets. The inclusion of the parameter q allows for the q-rung orthopair fuzzy sets to capture a broader range of uncertainty of information. In this paper, we present two novel distance measures for q-ROFSs inspired by the Jensen–Shannon divergence, called DJS_2D and DJS_3D, and we analyze some properties they satisfy, such as non-degeneracy, symmetry, boundedness, and triangular inequality. Then, the normalized distance measures, called DJS_2D˜ and DJS_3D˜, are proposed and we verify their rationality through numerical experiments. Finally, we apply the proposed distance measures to practical scenarios, including pattern recognition and multicriteria decision-making, and the results demonstrate the effectiveness of the proposed distance measures.

Source: Symmetry

DOI: 10.3390/sym16050574

Authors: Donglai Wang, Yige Yuan, Zhe Liu, Sijia Zhu, Zhifang Sun

Institutions: Hainan University, Universiti Sains Malaysia, Jiangsu Normal University, Shandong University of Engineering and Vocational Technology

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,728

OpenAlex ID: W4396693220

FWCI: 6.308

Cites: 45

Cited by: 28

Related to: 10