Abstract
In this paper, we investigate an analysis of expected utility based on fuzzy interval data. We establish a data processing method that can treat fuzzy interval data. Unfortunately, the method that direct usage of membership functions of fuzzy interval data has the problems of the efficiency when we carry out a calculation. To solve such problems, we propose a practical method that uses the midpoints of membership functions as the representative values.
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References
T.Okuda, Y.Kodono and K.Asai:Statistical Estimates based on Fuzzy Observation Data, Transactions of the Society of Instrument and Control Engineers, Vol.26, No.5, pp.564–571(1990).
L.A.Zadeh:Probability Measures of Fuzzy Events, Journal of Mathematical Analysis and Applications, 28, pp.421–427(1965).
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© 2003 Springer-Verlag Berlin Heidelberg
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Yoshikawa, Si., Okuda, T. (2003). An Analysis of Expected Utility based on Fuzzy Interval Data. In: Multi-Objective Programming and Goal Programming. Advances in Soft Computing, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36510-5_42
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DOI: https://doi.org/10.1007/978-3-540-36510-5_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00653-4
Online ISBN: 978-3-540-36510-5
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