Sentence examples for space for model from inspiring English sources

The answer must be yes, because a growing number of homeowners are finding space for model trains, yards of track, diminutive buildings and miniature landscape components.

We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure.

In order to systematically search the parameter space for model calibration in a reproducible manner, we used the Simulated Annealing (SA) algorithm, a commonly used engineering optimization technique [33].

As the implicit search space for model structure may be huge, to effectively perform such exploration we use evolution strategy (ES); once we determine the model structure, quantitative model learning (QuatML) described in Sect.

However, if the size of the dead zone is not too large, in particular if the linear approximation of the sway angles is still valid, then we can expect that the areas of stability in the parameter space for Models 3 and 4 are basically the same.

This creates an exciting space for modeling crawling motion from the microscopic to the macroscopic level.

Classification proposed in this paper is more precise and takes into account both the type of model elements and the size of space used for model creation.

In 1994, the SFP was first introduced by Censor and Elfving [22], in finite-dimensional Hilbert spaces, for modeling inverse problems which arise from phase retrievals and in medical image reconstruction.

In 1994, Censor and Elfving [1] first introduced the S F P in finite-dimensional Hilbert spaces for modeling inverse problems which arise from phase retrievals and in medical image reconstruction [2].

In 1994, Censor and Elfving [1] first introduced the SFP in finite-dimensional Hilbert spaces for modeling inverse problems which arise from phase retrievals and in medical image reconstruction [2].

In 1994, Censor and Elfving [1] first introduced the split feasibility problem (SFP) in finite-dimensional Hilbert spaces for modeling inverse problems which arise from phase retrievals and in medical image reconstruction [2].