Affiliation:
1. School of Mathmatics, Northwest University, Xi’an, P.R. China
Abstract
We analyze the properties and characteristics of the information structure in incomplete lattice-valued information system (ILIS), we redefine the information structure and the dependence and information distance between the two information structures. In addition, in order to evaluate the uncertainty of ILIS, the concepts of granular measure and entropy measure are expounded, including information granulation, information quantity, rough entropy and information entropy. Finally, we carry out numerical experiments to verify the feasibility of the method, and carry out effective statistical analysis. These results are conducive to the establishment of granular computing framework in ILIS.
Reference32 articles.
1. Furqan S. , Saleem N. and Sessa S. , Fuzzy n-Controlled Metric Space, in. Int. J. Anal. Appl. 21(101) (2023)
2. Li W. , Yang B. and Qiao J. , (O,G)-granular variable precision fuzzy rough sets based on overlap and grouping functions, in: Computational and Applied Mathematics 42(107) (2023).
3. Relationships between knowledge bases and related results;Li;Knowl Inf Syst,2016
4. Knowledge structures in a knowledge base;Li;Exp Syst,2016
5. Information granules and entropy theory in information systems;Liang;in: Sci China (Ser F),2008