Sentence examples for predictive computing from inspiring English sources

3. Multi-touch requires computational resources better used on predictive computing efforts, like predictive word typing algorithms.

We'll see predictive computing combine with more intuitive interfaces and speech recognition, devices like the Amazon echo and Siri to make the internet surround us.

What Robert Scoble calls "contextual computing" and Om Malik calls "predictive computing," will have the power to cut through the clutter as long as the messaging feels as though it was sent from the user to the user.

One of these is likely to be LinkedIn's Connected app, which has already been incorporating some elements of predictive computing to provide some insights and flag when you're near people in your network, aimed at those using the app on the go and in work environments.

From machine intelligence to predictive push computing to data analytics to mobile/wearable and more, it's becoming virtually impossible for a single developer to program across the modern full stack.

Specifically, they involve dividing predictive ability computed from an RR-BLUP model, assuming that genotypes are correlated, by the square root of heritability computed from a model assuming that genotypes are uncorrelated.

The controller (the Generalised Predictive Controller) computes at each sampling time the thermal flux to be exchanged with the thermal fluid flowing in the jacket to achieve the desired reactor temperature profile.

Normative data were established and predictive models computed for both children and adults.

To our knowledge, all available SNV classification tools base their inferences on predictive features computed when a custom dataset is input to the system (almost always using third-party databases and software).

In this short note however, we focus on the interest of computing predictive secular variation models as the average rate of change of the main field over the previous five years as given by retrospective models.

In this study, the performances of two well-known soft computing predictive techniques, artificial neural network (ANN) and genetic programming (GP), are evaluated based on several criteria, including over-fitting potential.