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Fuzzy estimators in expert systems. (English) Zbl 1246.62130

Summary: 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.

MSC:

62G86 Nonparametric inference and fuzziness
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
62G05 Nonparametric estimation
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