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Exact(29)
Computational results indicate that the proposed method is competitive.
The present results indicate that the method is competitive with well-established numerical algorithms.
Consequently, the achieved numerical results demonstrate that the proposed method is competitive with other well-established metaheuristic methods.
We also benchmark efficiency (i.e. error as a function of computing time) against the SPME method, which indicates that our method is competitive.
Optimization results show that the proposed method is competitive with other state-of-the-art metaheuristic algorithms presented in the literature.
This dynamic identification method is competitive with existing reduction methods, since it does not require system linearization or any a priori information about the system under study.
Similar(31)
Comparisons with other methods showed that the proposed method was competitive in predicting DNA-binding sites on unbound proteins.
The performance achieved by our identification method was competitive with previously published results in the overall precision of recall.
The new methods are competitive when compared with classical codes and when comparing with special codes.
Empirical evidence on a variety of benchmarks shows that both methods are competitive.
Findings indicate that lattice Boltzmann methods are competitive in terms of accuracy to approaches relying on a direct numerical solution of the Navier Stokes equations.
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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