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This paper focusses on the effects of dependence between the maximum rainfalls for different durations on the estimation of DDF curves and the modelling of uncertainty of these curves.
Variability arises from both ecological processes and sampling, requiring the modelling of uncertainty, the very nature of statistics [ 1, 2].
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However, there is an extensive body of literature focused on graded, or quantitative, models of uncertainty (Huber 2009; Halpern 2003).
Info-gap models of uncertainty are particularly useful when data on the uncertainties are quite limited.
Moreover, aspects of knowledge representation such as the modeling of uncertainty are discussed.
Unlike the modeling of uncertainty in stochastic programming, the uncertainty model in robust optimization is typically depicted as an uncertainty range.
In the UFZ I've been engaged in issues connected with the uncertainty in the hydrological, ecological, and socioeconomic data, models of uncertainty, and how the uncertainties may influence the possibility of achieving sustainable river basin management.
For trading off between the two performance objectives, they formulate the problem as a mixed integer programming model with explicit probability modeling of uncertainty.
It can be seen that when different models of uncertainty are used, the corrections of WT and PV output are different.
Stochastic analysis refers to the study and modeling of uncertainty with the objective of understanding its impact on performance, and is typically adopted in high risk projects.
Info-gap models of uncertainty are used to represent uncertainty in the power spectral density of the load and in parameters of the vibration model of the structure.
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CEO of Professional Science Editing for Scientists @ prosciediting.com