Shah, Nasir and Ali, Muhammad Irfan and Shabir, Muhammad and Ali, Abbas and Rehman, Noor (2020) Uncertainty measure of Z-soft covering rough models based on a knowledge granulation. Journal of Intelligent & Fuzzy Systems 38 (2020) 1637–1647, 38 (2). pp. 1637-1647. ISSN ISSN 1064-1246 (P)
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Abstract
Z-soft rough covering models introduced by zhan et al are important generalizations of classical rough set theory
to deal with more complex problems of real world. So far, the existing studies mainly focus on constructing various forms
of approximation operators and their related properties by means of neighborhoods. In this paper, we introduce different
kinds of uncertainty measures related to Z-soft rough covering sets and discuss their limitations. An axiomatic definition of
knowledge granulation for soft covering approximations space is introduced. Some main theoretical results are obtained and
investigated with the help of examples. Finally, a fully developed example describing the application of the proposed theory
in multicriteria decision making is constructed.
| Item Type: | Article |
|---|---|
| Additional Information: | Nil |
| Uncontrolled Keywords: | Z-soft rough covering sets, uncertainty, knowledge granulation, axiomation, decision making |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Faculty of Engineering and Applied Sciences (FEAS) > Department of Basic Sciences Islamabad |
| Depositing User: | Mr Abbas Ali |
| Date Deposited: | 26 Oct 2020 15:51 |
| Last Modified: | 26 Oct 2020 15:51 |
| URI: | http://research.riphah.edu.pk/id/eprint/991 |
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