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To test statistical significance in the normalized data series, we first estimated the uncertainty distribution of past exposure.
A natural way to handle the randomness is to admit that a given probability density function represents the uncertainty distribution.
This process results in a geological representation based on fuzzy logic and in maps of model uncertainty distribution.
It is proved that the possibility-constrained model can be transformed to an equivalent deterministic transportation model using inverse uncertainty distribution.
To determine the uncertainty distribution profile for annual energy use, a Monte Carlo method is applied to sample the possible combinations.
The molecular entropy displacement and cross-entropy quantities are used as probes of changes in the electron uncertainty distribution during the bond formation process.
Besides the uncertainty distribution, we present the regular uncertainty distribution as follows, which is used more often.
Since ξ is an uncertain variable with regular uncertainty distribution (Phi(t)), its inverse uncertainty distribution (Phi^{-1} alpha)) continuously exists from Definition 4 and Definition 5.
Furthermore, the use of the uncertainty distribution, works as a sufficient and necessary condition for the given utility function about the kind of uncertainty distribution which it follows.
Then the inverse function (Phi^{-1} alpha )) is called the inverse uncertainty distribution of ξ.
Let ξ be an uncertain variable with regular uncertainty distribution (Phi(t)).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com