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- W2050054736 abstract "Abstract We present a novel model reduction methodology for the approximation of large-scale nonlinear systems. The methodology stems from the need to find computationally efficient substitute models for nonlinear systems. The nonlinear system is viewed as a grey-box model with a mechanistic (first-principle) component and an empirical (black-box) component identified for the computationally intensive parts of the nonlinear system. The mechanistic part is approximated using proper orthogonal decompositions whereas the empirical part is identified as polynomial functions by parameter estimation using the reduced order mechanistic part." @default.
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- W2050054736 date "2007-01-01" @default.
- W2050054736 modified "2023-10-17" @default.
- W2050054736 title "MODEL REDUCTION OF NONLINEAR SYSTEMS: A GREY-BOX MODELING APPROACH1" @default.
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- W2050054736 doi "https://doi.org/10.3182/20070822-3-za-2920.00061" @default.
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