AbstractPrincipal Component Analysis has demonstrated promise in its ability to identify the low-dimensional chemical manifolds of turbulent reacting systems by providing a basis for the a priori parameterization of such systems based on a reduced number of parameterizing variables. Previous studies on PCA have only mentioned the importance of data pre-processing and scaling on the PCA analysis, without detailed consideration. This paper assesses the influence of data-preprocessing techniques on the size-redu…
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