Multiresolution Fuzzy Rule Systems

This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that handles the problem of granularization of the input space by using multiresolution linguistic terms. Models of different resolutions are chained by antecedents because linguistic terms of a level j are obtained by refinements of linguistic terms of a superior level j + 1. The models can also be chained by consequents using aggregation procedures. The family of models are called Multiresolution Fuzzy Rule Systems. A metasemantics based on linguistic operators is proposed for the interpretation of the refinements as a rule specialization. Interesting models result allowing local refinement of rules that preserve the semantic interpretation.