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Fuzzy Prediction Models in Measurement

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2 Author(s)
Leonid Reznik ; Dept. of Comput. Sci., Rochester Inst. of Technol., Rochester, NY ; Vladik Kreinovich

The paper investigates the feasibility of fuzzy models application in measurement procedures. It considers the problem of measurement information fusion from different sources, when one of the sources provides predictions regarding approximate values of the measured variables or their combinations. Typically, this information is given by an expert but may be mined from available data also. This information is formalized as fuzzy prediction models and is used in combination with the measurement results to improve the measurement accuracy. The properties of the modified estimates are studied in comparison with the conventional ones. The conditions when fuzzy models application can achieve a significant accuracy gain are derived, the gain value is evaluated, and the recommendations on fuzzy prediction model production and formalization in practical applications are given.

Published in:

IEEE Transactions on Fuzzy Systems  (Volume:16 ,  Issue: 4 )