Abstract

Experts are using picture fuzzy sets (PFSs) in their probes to resolve the uncertain and vague information during the process of decision making because PFSs describe human attitudes naturally. Divergence measure (DM) plays a dominant role in discriminating between two distributions of probability and extracting consequences from that discrimination. In the present work, a novel picture fuzzy divergence measure (PF-DM) is developed between two PFSs. Some of the suggested measure’s important qualities are also discussed with particular situations to validate it. Based on the suggested PF-DM, a multiple-criteria decision-making (MCDM) model is established to grab the fuzzy information. The suggested measure’s performance is compared to that of various existing measures in the literature. An MCDM model has been proven for the usefulness of the suggested technique in dealing with real-life scenarios in the context of dengue sickness and pattern identification. Validation of the suggested MCDM model has been further investigated using validity testing. To improve the generated model, a thorough comparison with several current methodologies has been carried out while taking the time complexity (TC) factor into account.

Highlights

  • Handling vagueuncertain information in real-life situations has trouble. erefore, various techniques, such as the theory of fuzzy sets (FSs), have been examined to address the ambiguity and uncertainty found in the real world

  • Because determining which option is the best match for a particular choice issue is impractical in real life, Wang and Triantaphyllou [32] developed testing criteria to examine the validity of multiple-criteria decisionmaking (MCDM) approaches, which are as follows

  • A picture fuzzy (PF)-Divergence measure (DM) is proposed in this study, along with proof of its validity, and some of its features are studied

Read more

Summary

A Novel Multiple-Criteria Decision-Making Approach Based on Picture Fuzzy Sets

Experts are using picture fuzzy sets (PFSs) in their probes to resolve the uncertain and vague information during the process of decision making because PFSs describe human attitudes naturally. A novel picture fuzzy divergence measure (PF-DM) is developed between two PFSs. Some of the suggested measure’s important qualities are discussed with particular situations to validate it. Based on the suggested PF-DM, a multiple-criteria decisionmaking (MCDM) model is established to grab the fuzzy information. E suggested measure’s performance is compared to that of various existing measures in the literature. An MCDM model has been proven for the usefulness of the suggested technique in dealing with real-life scenarios in the context of dengue sickness and pattern identification. Validation of the suggested MCDM model has been further investigated using validity testing. To improve the generated model, a thorough comparison with several current methodologies has been carried out while taking the time complexity (TC) factor into account

Introduction
Basic Concepts
Novel Divergence Measure for PFSs
MCDM Process Based on PF-DM
B2 B3 B4 B5
Validity Testing of Criteria for the Proposed MCDM Model
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call