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Better convergence is achieved by using the exact gradient of the log likelihood.
Memetic algorithms (MAs) are widely recognized to have better convergence capability than their conventional counterparts.
The boundary conditions were modified to achieve a better convergence of the solver.
The one with the weaker singularity has better convergence and gives more accurate results.
To alleviate this problem, a multi-domain spectral collocation method is developed which exhibits better convergence.
An even better convergence of O ϵ1) holds for square shaped pore-walls.
Overall, the Rosetta models show better convergence, and convergence for all groups correlates strongly with their similarity to the X-ray structures (Fig. 4b).
The proposed algorithm results in clustering the data sets with reduced error rate and better convergence rate.
Comparative analysis shows that the proposal finds suitable solutions for the OLNLDOP with a better convergence time.
The VNS method was compared with a multi-start algorithm in terms of performance, showing better convergence rates.
In addition, better convergence is also achieved for bending loading (when compare with the case of tension).
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