Linguistic Knowledge Representation for Stochastic Systems
نویسنده
چکیده
The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh’s definition, is proposed to formulate a linguistic fuzzy model of a stochastic system. The linguistic inference procedures and the exemplary MISO model are presented.
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