Rough Set Method Based on Multi-Granulations


The original rough set model is concerned primarily with the approximation of sets described by single binary relation on universe. In the view of granular computing, classical rough set theory is researched by single granulation (static granulation). The article extends the Pawlak rough set model to rough set model based on multi-granulations MGRS, where the set approximations are defined by using multi-equivalences on the universe. Mathematical properties of MGRS are investigated. It is shown that some properties of Pawlak rough set are special instances of MGRS, approximation measure of set described by using multi-granulations is always better than by using single granulation, which is suitable for describing more accurately the concept and solving problem according to user requirement

DOI: 10.1109/COGINF.2006.365510


Citations per Year

84 Citations

Semantic Scholar estimates that this publication has 84 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Qian2006RoughSM, title={Rough Set Method Based on Multi-Granulations}, author={Y. H. Qian and J. Y. Liang}, journal={2006 5th IEEE International Conference on Cognitive Informatics}, year={2006}, volume={1}, pages={297-304} }