Uncertainty measure of Z -soft covering rough models based on a knowledge granulation
Nasir A. Shah, Muhammad İrfan Ali, Muhammad Shabir, Abbas Ali, Noor Rehman · Journal of Intelligent & Fuzzy Systems · 2019
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.