The role and properties of rule relevancy in fuzzy inference process
نویسنده
چکیده
Fuzzy inference process usually involves the use of fuzzy rule base consisting in several fuzzy rules. Overall output can be obtained by aggregation of outputs of all rules. To obtain an output of individual rule the relevancy of this rule is calculated. Then the individual output is obtained from the relevancy and the consequent of the rule. Such process can be realised using an operator that is called the relevancy transformation operator. It must fulfil some requirements, which are tightly connected with an aggregation step. The properties of such operators are studied.
منابع مشابه
Information boundedness principle in fuzzy inference process
The information boundedness principle requires that the knowledge obtained as a result of an inference process should not have more information than that contained in the consequent of the rule. From this point of view relevancy transformation operators as a generalization of implications are investigated.
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