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Research on linguistic multi-attribute decision making method for normal cloud similarity

Authors :
Changlin Xu
Li Yang
Source :
Heliyon, Vol 9, Iss 10, Pp e20961- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Aiming at the uncertainty linguistic transformation problem in multi-attribute decision making, a decision-making method based on normal cloud similarity was proposed. Firstly, starting from the normal cloud characteristic curves, a normal cloud similarity measurement method based on Wasserstein distance is proposed by combing with the normal cloud entropy-containing expectation curve, which is using the Wasserstein distance to characterize the similarity characteristics of probability distribution. The properties of the proposed similarity measure are discussed in the paper. Secondly, the performance of the proposed method is compared and analyzed with the existed methods by numerical simulation experiment and time series data classification experiment. The experimental results show that the proposed method has good similarity discrimination ability, high classification accuracy and low CPU time cost. Finally, the method was successfully applied into linguistic multi-attribute decision making, and TOPSIS thought is used to compare and rank the schemes, so as to realize the final decision.

Details

Language :
English
ISSN :
24058440
Volume :
9
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Heliyon
Publication Type :
Academic Journal
Accession number :
edsdoj.38cd6bb0332489e88b8b66f8cdb64e4
Document Type :
article
Full Text :
https://doi.org/10.1016/j.heliyon.2023.e20961