In this contribution we carry out an analysis of the rule weights and Fuzzy Reasoning Methods for Fuzzy Rule Based Classification Systems in the framework of imbalanced data-sets with a high imbalance degree. We analyze the behaviour of the Fuzzy Rule Based Classification Systems searching for the best configuration of rule weight and Fuzzy Reasoning Method also studying the cooperation of some...

In case of fuzzy reasoning in sparse fuzzy rule bases, the question of selecting the suitable fuzzy similarity measure is essential. The rule antecedents of the sparse fuzzy rule bases are not fully covering the input universe therefore fuzzy reasoning methods applied for sparse fuzzy rule bases requires similarity measures able to distinguish the similarity of non-overlapping fuzzy sets, too. ...

In this paper we use an interpretation of fuzzy if-then rules to consider the notion of fixed points that are also called fix mundis in the literature invented by Fathi/Temme. We review some known results on fixed points of fuzzy ifthen rules and add more new ones and bring up the notion of fixed points in fuzzy chaining syllogism and we obtain new and interesting conclusions. Finally we bring ...

This paper presents an integrated knowledge-based system, which combines fuzzy rule-based reasoning with case-based reasoning, for turbomachinery diagnosis. By incorporating a casebased reasoning sub-system in a fuzzy rule-based system, the integrated system allows past experience to be applied in a more direct way. This helps improve the diagnostic accuracy of the rulebased system. This approa...

Most active research in Host and Network-based Intrusion Detection (ID) and Intrusion Prevention (IP) systems are only able to detect and prevent attacks of the computer systems and attacks at the Network Layer. They are not adequate to countermeasure XML-related attacks. Furthermore, although research have been conducted to countermeasureWeb application attacks, they are still not adequate in ...

Evolving fuzzy systems are data-driven fuzzy (rule-based) systems supporting an incremental model adaptation in dynamically changing environments; typically, such models are learned on a continuous stream of data in an online manner. This paper advocates the use of visualization techniques in order to help a user gain insight into the process of model evolution. More specifically, rule chains a...