Sentence examples for dynamically learning from inspiring English sources
This problem targets at dynamically learning user preferences regarding the perceived QoS level per service/application and potentially, the maximum acceptable price per service/application [31].
More information regarding the mathematical formulation and the algorithm for the functionality for dynamically learning user preferences, as well as the data structures and elements it utilises can be found in [31].
The main innovation of the study presented in this article lies in the fact that the article presents an approach for dynamically learning both context information and user preferences, the combination of which could be exploited in a later stage for the selection of the most appropriate network configuration.
The method dynamically learns a color model of elephants from a few training images.
Ideally, it should be dynamically learned and adjusted without any a priori knowledge [31].
The method dynamically learns a colour model of elephants from a few training images and, then, localizes elephants in video sequences with different backgrounds and lighting conditions.
Neural networks can dynamically learn the behavior of an elevator system and predict the next floors to stop, based on what has been learnt.
In some auctions, the seller may be uncertain about the market response and hence may want to dynamically learn the demand by observing the number of posted bids.
More complex approaches could be developed that dynamically learn the features of when the RSS measurements are changing, using this to partition the data to generate different models for different times of the day.
The outcoming system, observing all the users during their network interactions, dynamically learns the behavioral patterns of each one, and it is able to evaluate their trustworthiness in the network.
In all, supervised learning algorithms enable context-aware applications and systems to keep a trace of their previous observed experiences in the form of trained classes of context and employ them to dynamically learn the parameters of the stochastic context models (a pattern that may be analyzed statistically but not predicted precisely).
