Sentence examples for model our system from inspiring English sources

Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

While in this experiment the correct transcription of the response was always in the language model, our system must also be able to reject utterances when they are not present in the language model, while still accepting correctly recognized utterances.

Considering that we model our system as distributed data stream system, some software components are concerned with communication issues, while other are concerned with processing issues (i.e., the analysis, aggregation and transformation the data stream).

On that basis, we model our system as an absorbing Markov chain [16, Chapter 8] with transient states and one absorbing state defined as follows (see, Figure 3): (53).

For a scene with large amount of triangles, for example, the scene shown in Figure 5 containing 623805 triangles (including vascular models, skeleton model, and C-arm model), our system still maintains nearly 60 FPS, which is suitable for an interactive simulation environment.

Unlike other existing models, our system is fast adaptable to different application domains and it is highly interpretable.

The latter models our system as a closed queuing network considering multiple resources, different classes of devices based on their service request patterns and multiple workload mixes [18].

Following these steps, we modeled our system as a random process (see Table S1 and Fig. S5 online).

The model of our system is shown in Fig. 2.

We used these absolute abundance measurements to prepare an approximate quantitative model in our system.

In Section System model, we describe our system model.