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A large set of test problems has been simulated and analyzed to assess the validity of our approach in terms of both accuracy and efficiency (CPU time and memory consumption).
The numerical results, which have been collected on a large set of test problems, demonstrate the validity of the proposed model, particularly in dealing with the trade-off between quality of service and costs management.
Superiority of the proposed solution approach has been verified by computational experiments on a large set of test instances together with fair comparisons with two state-of-the-art algorithms.
All these parameters were manually optimized for best performance on a large set of test images.
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For that purpose, we have focused on providing a large set of tests that demonstrate how the proposed system works in many different situations.
Two multivariate methods, RF and PLS-DA, were shown to be useful to select the most informative items from a large set of testing instruments with high sensitivity and specificity, while allowing to characterize a set of 63 patients from a multivariate perspective.
To this aim we carried out a large set of tests by means of the yeast two hybrid technique which is a methodology widely used to evaluate the capacity of MADS transcription factors to hetero- and/or homo-dimerize in vitro [ 26, 27].
We use these parameters in our experiments and evaluate their performance for a larger set of test images.
A larger set of testing data is necessary to adequately describe performance.
The proposed method is shown to properly estimate the shear resistance of a large set of available test data, being able to account for most influencing parameters.
This paper presents a statistical approach for assessing general LV distribution network design strategies based on a large set of realistic test networks and optimal economic circuit design.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com