Rule reduction for efficient inferencing in similarity based reasoning

The two most important models of inferencing in approximate reasoning with fuzzy sets are Zadeh's Compositional Rule of Inference (CRI) and Similarity Based Reasoning (SBR). It is known that inferencing in the above models is resource consuming (both memory and time), since these schemes often consist of discretisation of the input and output spaces followed by computations in each point. Also an increase in the number of rules only exacerbates the problem. As the number of input variables and/or input/output fuzzy sets increases, there is a combinatorial explosion of rules in multiple fuzzy rule based systems. In this paper, given a fuzzy if

• Type: Journal
• Year: 2008
• Where: IJAR
• Authors: Balasubramaniam Jayaram
• Keywords: Fuzzy Sets, IJAR 2008, Rule Base, SBR Inference