| Autor: |
Le Sheng Jin, Zhen-Song Chen, Ronald R. Yager, Reza Langari |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-9 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1875-6883 |
| DOI: |
10.1007/s44196-023-00227-4 |
| Popis: |
Abstract More uncertainty can be obtained when real numbers are extended to intervals. The two new concepts proposed in this work are the natural extensions of cognitive interval information and cognitive uncertain information with real numbered values replaced by interval values. Hence, interval type cognitive interval information and interval type cognitive uncertain information with some characteristics, structures, uncertainty degree functions and score functions of them are analyzed. Two special usages of the two uncertain information types in group decision making show that they have much more algorithmic variations, flexibility and applicability than the mere formal extensions or changes. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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