Interval Granules in Incomplete Information Systems

Abstract:

Rough set theory is an efficient mathematical theory for data reduction and knowledge discovery of various fields. However, classical rough set theory is not applicable for knowledge induction of incomplete information systems. In this paper, a concept of interval granule is presented. Based on this concept, the hierachical structure of knowledge granularity and approximation of rough sets in incomplete information systems are studied, and related properties are given. An example show that the interval granule have better results than existing models for knowledge induction and approximation.

• Periodical: Advanced Materials Research (Volumes 418-420)
• Pages: 1915-1918
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.418-420.1915
• Online since: December 2011
• Authors: Xiao Hui Chen, Ren Pu Li, Zhi Wang Zhang
• Keywords: Incomplete Information System, Interval Granule, Nested Sequence, Precision

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