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This model is 'validated' by carrying out a number of dynamic state simulations and then used for designing model based parametric controllers.
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A novel method is then proposed to derive the production capacity information representing the detail scheduling model based on parametric programming technique.
These methods are termed "model based" or "parametric" because they are based on statistical models of range evolution, whose parameters ("variables") are biogeographic processes such as dispersal, range expansion, or extinction.
One of the principal tasks of history based parametric modeling is to maintain the design history of parts.
In history based parametric CAD modeling systems, persistent identification of the topological entities after design modification is mandatory to keep the design intent by recording model creation history and modification history.
This model was used in a FE based parametric study focusing on the uncertainties related to the experiment.
To address the stochastic nature of transitions in cognition, our research group has developed a transition model based upon a parametric representation of a multistate Poisson model [ 14].
Besides transform-based methods mentioned above, non-parametric and parametric model based algorithms [5 7] also achieve good de-noising results.
The development of a parametric cost estimation model based on activity-based costing and process modeling provides a challenge for future research.
In this respect, a parametric model based on simplification of the Penman Monteith formulation is presented.
The best three parametric model, based on steric, 3D- and finger print descriptors, was found to have R2 = 0.91, R2ex = 0.89, and CCCex = 0.94.
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