A modified Apriori algorithm to generate rules for inference system with probabilistic-fuzzy knowledge base
نویسندگان
چکیده
In the article the possibility of applying one of the methods of data mining – fuzzy association rules to model fuzzy systems is presented. The algorithm of automatic extracting knowledge base is a modification of the Apriori algorithm. The obtained rules of the model contain weights, that are calculated on the basis of measures of fuzzy association rules and constitute probability of fuzzy events contained in the rules. The rules’ weights are employed during system inference. The method has been tested using exemplary data.
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