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Based on this definition, the expected value operator of birandom variable and chance measures of birandom event are further introduced.
In order to deal with the fuzzy coefficients in the objective functions, an expected value operator based on Me is employed.
A method is proposed in this paper using fuzzy weighted average method in the fuzzy expected value operator in order to rank technical attributes in fuzzy QFD.
By the expected value operator and chance constraint operator, the model has been transformed into a deterministic multi-objective mixed-integer non-linear programming model.
For dealing with uncertainties, a hybrid crisp approach with an expected value operator is proposed to convert the fuzzy random parameters into definitive parameters.
To deal with the uncertainty, the fuzzy numbers in the model are defuzzified by using an expected value operator with an optimistic pessimistic index.
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Such cullings bolster the average monthly revenue per user, the main bellwether used by investors to value operators.
Among others, we mention the description of Riesz transforms as principal value operators.
To show the reasonableness of the mean chance approach, we prove the expected value operators defined in this paper coincide with those presented in our previous work.
After discussing the duality of the mean chances, we use the mean chances to define the expected value operators of a fuzzy random variable via Choquet integrals.
For E = ℋ, the integrals ∫ E d m h = ∫ ℋ d m h in (49) coincide with the expected value operators E in (47).
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