Sentence examples for models that generates from inspiring English sources

Recent experiments [3] showed that today's online social networks such as Facebook indicate that the degree of separation (for almost any two individuals in a given database) must be even smaller than 4. The small-world model by Watts and Strogatz [4] was one of the first models that generates networks with small diameter.

Godley has little faith in predictions of an imminent recovery, or in the conventional forecasting models that generate them, which he describes as "absolutely useless".

Meteorologists at the National Weather Service and some independent weather companies, like AccuWeather and the Weather Channel, run the weather service information through computer models that generate forecasts.

It works quickly, pays modest salaries, and avoids creating what is known in the AIDS world as "gold-plated programs" — glossy models that generate more publicity and self-congratulation than results.

Contact models that generate sequences of microimpacts stochastically are well suited for generating complex impacts.

Like any for-profit enterprise, the social media giants operate under models that generate profit for their investors.

However, CloudSim provides some power models that generate power consumption values by implementing linear relationship between power consumption and CPU utilization [23].

The highly nonlinear rigorous models of the distillation column and phase change are being substituted with simple surrogate models that generate operating responses with adequate accuracy.

Asia's messaging apps have been around longer, and thus most have more mature business models that generate income by connecting brands with consumers, in addition to other non-marketing revenue streams such as games and stickers.

The comparison of the data removal models on the PKIS data set seems to lend further support to this hypothesis, as the performance progression is quite different between the models that generate complete but smaller data set and the label removal model that generates sparse data sets.

We provide an overview of a number of commonly used empirical specifications, the underlying theoretical models that generate them; and the conditions for the causal identification of parameters with cross-sectional data.