Similarity Measure Based on the Belief Function Theory: Application in a Decision-Making Process
- https://doi.org/10.2991/jsta.d.210111.002How to use a DOI?
- Belief function theory, Belief set, Similarity measure, Decision-making
This study considers a new aspect of the belief function theory to define a belief set, which is characterized by truth, uncertainty and falsity belief degrees as a 3D vector representation. Then, based on the implication of a belief set, one of the similarity measures (i.e., Cosine, Jaccard and Dice) between two belief sets is defined. Furthermore, the weighted similarity measure of these different species between each alternative and ideal alternative is presented in order to rank alternatives and determine the best one. Finally, a comparison between similarity measures and an application of a new method based on similarity measures between two belief sets in the decision-making process is calculated to show the capability and validity of the proposed method.
- © 2021 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - M. Khalaj AU - F. Khalaj PY - 2021 DA - 2021/01 TI - Similarity Measure Based on the Belief Function Theory: Application in a Decision-Making Process JO - Journal of Statistical Theory and Applications SN - 2214-1766 UR - https://doi.org/10.2991/jsta.d.210111.002 DO - https://doi.org/10.2991/jsta.d.210111.002 ID - Khalaj2021 ER -