Similarity Measure Based on the Belief Function Theory: Application in a Decision-Making Process
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 Dic...
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| Veröffentlicht in: | Journal of Statistical Theory and Applications 2021-03, Vol.20 (1), p.1-10 |
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| container_title | Journal of Statistical Theory and Applications |
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| creator | Khalaj, M. Khalaj, F. |
| description | 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. |
| doi_str_mv | 10.2991/jsta.d.210111.002 |
| format | Article |
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| language | eng |
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| subjects | Belief function theory Belief set Decision making Decision theory Research Article Similarity Similarity measure |
| title | Similarity Measure Based on the Belief Function Theory: Application in a Decision-Making Process |
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