On redundancies in systems of fuzzy/linguistic IFTHEN rules under perception-based logical deduction inference ?
In this study, we formally investigate how to determine fuzzy/linguistic IFTHEN rules that are redundant in linguistic descriptions (systems of IFTHEN rules). We present a formal definition of redundancy and show that seemingly redundant rules can in fact be indispensable. These results apply to IFTHEN rules that use evaluative expressions (e.g., small and very big) and the inference method called perception-based logical deduction. However, they are also valid for inference systems with compatible design choices. We also describe an algorithm for the automatic detection and removal of redundant rules. Finally, we present an example of a linguistic description that is learned automatically from data and reduced using our algorithm.
redundancy perception-based logical deduction linguistic description fuzzy ifthen rules