Information granularity in fuzzy binary GrC model
Authors: Yuhua Qian, Jiye Liang, Weizhi Wu, Chuangyin Dang
Abstract:
Zadeh's seminal work in theory of fuzzy-information granulation in human reasoning is inspired by the ways in which humans granulate information and reason with it. This has led to an interesting research topic: granular computing (GrC). Although many excellent research contributions have been made, there remains an important issue to be addressed: What is the essence of measuring a fuzzy-information granularity of a fuzzygranular structure? What is needed to answer this question is an axiomatic constraint with a partial-order relation that is defined in terms of the size of each fuzzy-information granule from a fuzzy-binary granular structure. This viewpoint is demonstrated for fuzzy-binary granular structure, which is called the binary GrC model by Lin. We study this viewpoint from from five aspects in this study, which are fuzzy BINARY-granular-structure operators, partial-order relations, measures for fuzzy-information granularity, an axiomatic approach to fuzzy-information granularity, and fuzzy-information entropies.
Keywords： Fuzzy-information entropy, fuzzy-information granularity, granular computing (GrC), partial-order relation
Information granularity in fuzzy binary GrC model.pdf
Thu Dec 15 10:50:00 CST 2011