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It is an effective tool for uncertainty modeling and reliability analysis with dependent evidence variables.
This paper proposes a novel evidence-theory model for multidimensional problems, with consideration of the dependence among evidence variables.
In the proposed analysis model, the uncertain parameters with imprecise data are treated as evidence variables, and the belief measure and plausibility measure are employed to evaluate system squeal instability.
A uniformity approach is used to deal with the evidence variables, through which the original reliability problem can be transformed to a traditional reliability problem with only random uncertainty.
The key idea of the proposed method is the use of the equivalent variables named as evidence-based fuzzy variables, which are special evidence variables with fuzzy focal elements.
In ETJEM, the response of acoustic system with evidence variables is approximated by Jacobi expansion, through which the repetitively extreme value analysis needed in evidence theory can be efficiently performed.
Similar(49)
In signal detection theory, the presentation of a stimulus is thought to give rise to a normally-distributed evidence variable.
Because of noise in the evidence accumulation process, this difference variable closely approximates the characteristics of the evidence variable postulated in Signal Detection Theory.
Note that the evidence
The mean value of the evidence variable depends on the stimulus condition; the value on a specific trial is thought to be distributed normally around this mean.
The effect of reward is to shift the position of this criterion relative to the distributions of evidence values, so that a greater fraction of trials contributing to each distribution fall on the high reward side of the criterion (this could also be achieved by a shift in the evidence variable in the opposite direction).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com