Fuzzy Estimators in Expert Systems
نویسندگان
چکیده
In this paper we consider the use of fuzzy estimators –a new and promising approach of estimating the parameters of a probability distribution from statistical samples– to represent mathematical knowledge in expert systems. A class of fuzzy estimators suitable for fuzzy arithmetics generalizes the existing approaches and it is used to derive the fuzzy estimators for the parameters of the normal distribution. The fuzzy binary operations of addition, subtraction, multiplication and division are defined, their explicit and unique membership functions are constructed, and a ranking method to deal with fuzzy comparisons is proposed. Finally, a Prolog-based implementation for performing fuzzy computational tasks is discussed.
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