Sentence examples for model decomposition and from inspiring English sources

The contribution of this methodology is to extend the formal model transformation framework toward building energy system modeling, thus enabling efficient and flexible system synthesis through model decomposition and recomposition.

This paper fills these gaps by presenting a methodology for automated product model decomposition and recomposition for climate-based daylighting simulation using Radiance.

In this paper we use concepts from systems theory to develop two complementary tools that can help us understand the complex behaviour of such system models: one based on model decomposition and one on model reduction.

A cluster usually uses a distributed memory system; therefore, model decomposition and communications between different processors (i.e. computer nodes) are required to be handled explicitly in the parallel code for a cluster.

Moreover, as these examples show, not only geometric zoom but also model decomposition and semantic zoom are important for multi-level visualization of huge models.

Supported by the CRNM method, an integrated multi-model control framework is developed, in which the multi-model decomposition and local controller design are closely integrated, model redundancy is avoided, computational load is reduced, and dependency on a prior knowledge is reduced.

As we will explain below, this one-to-one mapping between psychological processes and model parameters allows for an informative diffusion model decomposition of PES and a rigorous assessment of the extent to which each explanation (or, indeed, any combination of them) holds true.

A solving strategy incorporating model decomposition, model relaxation and case initialization is proposed to find a feasible solution.

Additionally, other widely accepted denoising methods based on wavelet transformation and empirical model decomposition are simulated to make a comparison.

V and U are matrices derived from the singular value decomposition (SVD) of the channel matrix H K. That is, if we apply SVD to the channel matrix H K, we obtain: H K = UΣ V H (8) Figure 2 Model decomposition with CSI at transmitter and receiver.

Local features based on Gaussian mixture model decomposition can be utilized to describe and compare gene expression patterns (Peng and Myers, 2004).