Sentence examples for model reduction approach from inspiring English sources

The method is a generalization of the well-known model reduction approach for systems with input delay.

In this paper, we develop a multiscale model reduction approach to couple gas flow and geomechanics in fractured shale media.

This paper presents a developed model reduction approach for the vibration analysis of hydraulic pipeline with long distance and multi-supports with elasticity popularly used in aircraft.

The model reduction approach is further tested by performing patient simulations under exercise and varying degrees of pathophysiological conditions based on reduction of reference solutions (rest and medium backflow conditions respectively).

The present work considers a model reduction approach for fault diagnosis with generalised likelihood ratio (GLR) method to improve upon its diagnostic performance and computational efficiency in large dimensional applications.

We demonstrate the model reduction approach with polycrystal microstructures and compute the variability of homogenized properties using a sparse grid collocation approach in the reduced-order space that describes the grain size and orientation variability.

In the current paper, we discuss how these global model reduction approaches can be combined with local techniques to speed-up the simulations.

This is a conceptually new development of model reduction approaches, which we think will stimulate much further research and will prove to be very useful in future modelling projects.

In a previous work (Romero-Ugalde et al., 2013 [1]), we focused on the topic of providing balanced accuracy/complexity models by proposing a dedicated neural network design and a model complexity reduction approach.

Finally, the presented method is generalized for a condition in which a limited number of sensors are installed on the structure using Neumann Series Expansion-based Model Reduction (NSEMR) approach.

The log Bayes Factor for this model equals 16.55 when compared to the independent model, which is just below the log Bayes Factor generated by the optimal model using the likelihood-based reduction approach, although the two model performances are not significantly differing from one another.