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Combining these formulas with the conditional extremum method gives several optimization equations corresponded to different optimization objectives.
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In the experimental discussion, the paper gives several reasons why the proposed method outperforms others.
Section 4 gives several examples to test the proposed method.
Locke gives several lists.
Results show that the proposed method gives good performance on several publicly available datasets in terms of detection accuracy and recognition rate.
This method gives convincing results for several types of porous graphites with initial densities from 1.77 to 2.21 g cm−3, and allows to explain the disparities between their corresponding Hugoniot curves and the one of pure diamond at high pressure.
A quantitative quality measure called efficacy is constructed and shows that the new method gives improved partitioning for several metabolic networks, including bacterial, plant and mammal species.
The Moroccan food authority Paula Wolfert, from whom I learned this method, gives instructions for it in several of her books.
The same method gives a new proof of recent results of Katznelson-Tzafriri. Several applications are given.
In this paper, we give several systematic methods for discretizing general multi-symplectic formulations of Hamiltonian PDEs, including a local energy-preserving algorithm, a class of global energy-preserving methods and a local momentum-preserving algorithm.
Advocates give several reasons.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com