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Gaussian process emulators of computationally expensive computer codes provide fast statistical approximations to model physical processes.
Soft computing approaches using training data are good approximations to model the different systems.
The methodology of Part 1 is applied for the discrete and finite element approximations to model the horizontal behaviour of an agricultural spray boom.
Further, the choice of using linear approximations to model temporal information within voiced speech segments, while the simplest, may not be optimal and is an avenue for future work.
Crucially, both rest on model selection: In DCM this involves comparing the evidence for different models directly [ 38], while model selection in GC is implicit in the test for the presence of GC — and also arises in the selection of VAR model order, using standard approximations to model evidence, such as the Akaike or Bayesian information criteria [ 42].
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Second, my response to Yonezawa and Hasegawa [ 120] provides an explanation of why my independent ancestry models are reasonable approximations to models explicitly incorporating convergence due to physical constraints and selection for function.
The Kerr metric can be used, to good approximation, to model the spacetime background around the rotating planet [9].
The Sugeno adaptive fuzzy neural network using training data is a good approximation to model different systems.
The scale separation enables use of the eikonal (ray-tracing) approximation to model the RF wave propagation.
The plus sign represents the use of a Bruggeman effective medium approximation to model the refractive index of the mixture of materials in the layer.
Our simulations rely on density functional theory and a mean-field approximation, the virtual crystal approximation, to model the highly alloyed system.
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