Sentence examples for inputs of interest from inspiring English sources

Although the increasing computer power makes the numerical solution problems of very large dimensions that model complex phenomena essential, a computational reduction is still determinant whenever interested in real-time simulations and/or repeated output evaluations for different values of some inputs of interest.

The mechanism discussed in this paper facilitates selective triggering of higher layer neurons which serves as target ensemble for evaluation of a particular input of interest.

Joly et al. [ 55] propose a logic model approach which focuses on inputs, strategies, outputs, and multiple level outcomes, with emphasis on accredited public health agencies as the input of interest.

One way to carry out this type of analysis, called clamping technique [ 29], consists of comparing the error made by the network from the original patterns with the error made when restricting the input of interest to a fixed value (in general the average value) for all patterns.

This paper introduces a methodology to simplify the uncertainty analysis of large-scale problems where many outputs and/or inputs are of interest.

In our analysis we change each input parameter by plus, respectively, −10 % compared to its original value estimated by the experts while keeping all other input parameters constant, and repeat this procedure with every input parameter of interest.

Evaluation of the trained neural network models provided information on the relative importance of individual input variables, allowing us to further identify those inputs of particular interest in this kind of work and to gain a better understanding of the processes linking soils and their environment.

For a given number of input variables of interest, a series of the proposed designs with various run-sizes is obtained and collected in a catalogue.

The input Regions of Interest (ROIs) are segmented manually and further subjected to a number of preprocessing stages.

Systems are generated by grouped input parameters of interest to the unit costs of solar power and product water.

The RER development uses general error regression models to determine the best fit relationship between root cause consequence and likelihood values and the input factors of interest.