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Kybernetika 38(3):327-338, 2002.

Information Boundedness Principle in Fuzzy Inference Process.

Peter Sarkoci and Michal Šabo


Abstract:

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.


AMS: 04A;


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BIB TeX

@article{kyb:2002:3:327-338,

author = {Sarkoci, Peter and \v{S}abo, Michal},

title = {Information Boundedness Principle in Fuzzy Inference Process.},

journal = {Kybernetika},

volume = {38},

year = {2002},

number = {3},

pages = {327-338}

publisher = {{\'U}TIA, AV {\v C}R, Prague },

}


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