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Correlations are based on the covariance between two variables, which is a function of the variances of the two variables.
As the output of DERs is usually unpredictable, the scheduling of VPPs has to deal with a number of uncertain variables, which is a fuzzy programming problem.
However, optimization methods based on the latter either need ad hoc low-fidelity model setup or have difficulties in handling problems with more than a few design variables, which is a main barrier for industrial applications.
We note that the functions in Λ k satisfy that their behavior is enveloped by the maximum and minimum functions of its variables, which is a common hypothesis in studying higher order nonlinear difference equations.
Another large group of studies only examined these variables as binary variables, which is a methodologically weak approach.
The RRR method combines the strengths of a priori and exploratory approaches (9) by using prior knowledge in the selection of response variables, which is a clear advantage.
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In practice, the model is applicable for finding disease- or other covariate-related effects across multiple paired measurements, from different sources having different variables, which is an increasingly common and important data-analysis task.
The root mean square variables, which were a measure of the undulations or noise in the signal [ 9], also increased with increasing disease severity.
The model uses a damage variable, which is a volumetric quantity, called the void-volume fraction.
We estimated our basic model using the Emergency Department variable, which is a binary variable equal to one if the admission originated in the Emergency Department of the hospital.
The proposed dissipative evolution laws are governed by an effective stress variable, which is a function of an equivalent pore pressure.
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