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Fuzzy decision tree induction is an important way of learning from examples with fuzzy representation. Since the construction of optimal fuzzy decision tree is NP-hard, the research on heuristic algorithms is necessary. In this paper, three heuristic algorithms for generating fuzzy decision trees are analyzed and compared. One of them is proposed by the(More)
If the given fact for an antecedent in a fuzzy production rule (FPR) does not match exactly with the antecedent of the rule, the consequent can still be drawn by technique such as fuzzy reasoning. Many existing fuzzy reasoning methods are based on Zadeh's Compositional Rule of Inference (CRI) which requires setting up a fuzzy relation between the antecedent(More)
High level Petri Nets have recently been used for many AI applications, particularly for modelling traditional rule-based expert systems. The major effect is to facilitate the analysis of the knowledge inference during the reasoning process, and to support the system verification which increasingly becomes an integral part of expert system development.(More)