Sentence examples for classes of attributes from inspiring English sources

This article first reviews the main classes of attributes, providing a survey of heuristics and meta-heuristics for Multi-Attribute Vehicle Routing Problems (MAVRP).

After the simulated realizations, the weighted "distances" attributes extreme values (probability classes) of each grid node are calculated and the MDS algorithm is applied for the spatial representation of the grid nodes in a new Cartesian reference frame based on the "distances" of the probability classes of attributes.

It includes most types of geometry, supports many classes of attributes (Eastman, 2012).

Four classes of attributes are considered: indirectly observable wine characteristics, directly observable wine characteristics, measures of wine quality, and winery characteristics.

The API programmer will then be able to ask for classes of attributes from classes of identity provider rather than having to specifically list them all e.g. request a credit card attribute from a bank, rather than a Visa card attribute from HSBC or a MasterCard attribute from Barclays Bank.

Specific classes of attribute were created using this hierarchy for the counts (number_of_insertions, number_of_deletions, number_of_stops, number_of_shifts, disablements and polyA) and scores (log_kimura_score, fraction, evalue and identity) we wanted to track.

These datasets were collected from the the KEEL [21] and UCI [22] machine learning repositories and represent a variety of complexity, number of classes, number of attributes, number of instances, and imbalance ratio (ratio of the size of the majority class to the minority class).

3. Using the article as a resource, create a class list of attributes that make Cartier-Bresson's photographs so successful (e.g. "cropping the image to create a desired effect" or "recognizing the significance of an event").

And according to Wolff, there are three basic classes of accidents: proper attributes, common attributes, and modes.[73] Proper and common attributes of substance follow from and are determined by a thing's essentials.

Two key ideas are addressed in this study: (i) the use of stochastic simulations to generate a local cumulative distribution function or extreme classes of each attribute and (ii) the use of a multidimensional scaling (MDS) technique to visualize and quantify the relative importance of each attribute in the classification process.

Traffic engineering with link coloring (TELIC) was proposed to automatically assign LSPs in multi-protocol label switching domain based on bandwidth and class of service attributes.