A synthesis of fuzzy rule-based system verification

We give a synthesis of methods proposed in literature that try to extend the verification of classical rule bases to the case of fuzzy knowledge modeling. We identify two dual lines of thought respectively leading to static and dynamic anomaly detection methods. The major outcome of the confrontation between both approaches is that their results, stated in terms of necessary and/or sufficient conditions are difficult to reconcile. The paper addresses precisely this issue by presenting a theoretical framework which enables us to effectively evaluate the results of both static and dynamic verification theories