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The theoretical results are also confirmed by some numerical experiments.
Rigorous stability estimates are proved and the accuracy of the algorithm is illustrated also by some numerical experiments.
A genetic algorithm is designed to solve the general maximum entropy model for discrete fuzzy variables, which is illustrated by some numerical experiments.
The stability and the oscillatory behaviour of the schemes are carefully studied and the analyses are completed by some numerical experiments.
We prove the convergence of the method and confirm the theory by some numerical experiments.
By some numerical experiments we can conjecture that the lower bound (3.1) holds true also when and, in particular, for these values of we have.
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Finally, the benefit of the proposed result is validated by using some numerical experiments.
The ideas discussed in this paper have been implemented into a software package by which some numerical experiments are reported.
We develop a geometric CG method for solving the IVA problem and conclude by providing some numerical experiments.
We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.
We study some properties of the new operators and, by means of some numerical experiments, we present their use in practical computation and we show the superiority with respect to the few other approaches previously proposed in literature.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com