Fuzzy reasoning model under quotient space structure

Authors:
Ling Zhang;Bo Zhang
Affiliations:
Artificial Intelligence Institute, Anhui University, Hefei, Anhui 230039, China;Department of Computer Science & Technology, Tsinghua University, Beijing 100084, China
Venue:
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Dealing with uncertainty in data mining and information extraction
Year:
2005

Citing 7
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Abstract

In this paper, we present a theoretical framework of fuzzy reasoning model under quotient space structure. It consists of (1) introducing quotient space structure into fuzzy sets, i.e., constructing fuzzy set representations of different grain-size spaces and their relationships; (2) introducing the concept of fuzzy sets into quotient space theory. i.e., introducing fuzzy equivalence relation and discussing its corresponding reasoning in different grain-size spaces: and (3) discussing the relationship and transformation among different granular computing methodologies. The framework proposed is aimed to combine two powerful abilities in order to enhance the efficiency of fuzzy reasoning: one is the ability of computing with words based on fuzzy set methodology, the other is the ability of hierarchical problem solving based on quotient space approach.