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Travel-time based models simplify the description of reactive transport by replacing the spatial coordinates with the groundwater travel time, posing a quasi one-dimensional (1-D) problem and potentially rendering the determination of multidimensional parameter fields unnecessary.
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The model simplifies the existing complex process models.
Secondly, these models usually simplify the meteorological process.
Automated modeling tools simplify the task of reduced-order modeling.
Another important limitation is the assumptions on which the analysis is based, which are necessary to simplify the model or need to be used in cases of incomplete data.
Based on the data-sets selected from different published work, a principal component analysis (PCA) is applied to select the significant modeling inputs and simplify the model structure.
In practical applications, the driver's body and the friction forces are difficult to be accurately described with a mathematical model; for this reason, the proposed controller is designed based on a model simplified from a 6-degree-of-freedom (6-DOF) seat-driver model with nonlinear friction.
Another important limitation is the assumptions on which the analysis was based, which may be necessary to simplify the model or in case of incomplete data.
Another important limitation is the assumptions on which the analysis is based, that may be necessary to simplify the model or in case of incomplete data.
Based on a method proposed to simplify the system model, an extended state space model predictive control is designed, which combines the feedforward strategy to eliminate the disturbance.
[44] presents a multi-PR current controller based on the circuit model, which simplifies the harmonic extraction unit.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com