This paper describes a method for rule base compression of fuzzy systems. The method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This rule base compression method outperforms significantly other known methods for fuzzy rule base reduction.Peer Reviewe

Gegov, Alexander

Gobalakrishnan, N.

English

Analysis and design of hierarchical fuzzy systems,

and R.Kisner, Hierarchical fuzzy control,

Complexity Management in Fuzzy Systems (Springer,

H.Chung and F.Yu, Modelling of hierarchical fuzzy systems, Fuzzy Sets and Systems,

Intelligence: A Guide to Intelligent Systems (Pearson,

J.Keane, Approximation capabilities of hierarchical fuzzy systems,

J.Lee, A class of hierarchical fuzzy systems with constraints on the fuzzy rules,

J.Lee, Universal approximation by hierarchical fuzzy system with constraints on the fuzzy rule, Fuzzy Sets and Systems,

Logic with Engineering Applications

On multistage fuzzy neural network modelling,

Scale Systems: Modelling, Control and Fuzzy Logic (PrenticeHall, Englewood Cliffs,

Software Tool for advanced Inference in Fuzzy system, BSc Final year Project (University of Portsmouth,

Advanced inference in fuzzy systems by rule base compression