Dealing with covering problems in fuzzy rule systems by similarity-based extrapolation

We propose a solution for overcoming possible lacks of covering of the input space in fuzzy rule bases. Our approach is based on similarity-based reasoning and considers a kind of extrapolative inference rule which enlarges the range of applicability of a fuzzy rule by replacing conditions in the premise of the form "X is A" by "X is approximately-A", where approximately-A is the image of A by a suitable fuzzy similarity relation.

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