Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
2014 ◽
Vol 2014
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pp. 1-6
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Keyword(s):
Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP) and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.
2006 ◽
Vol 157
(23)
◽
pp. 3055-3071
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2021 ◽
Vol 675
(1)
◽
pp. 012143
2017 ◽
Vol 25
(1)
◽
pp. 163