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The findings confirm the efficiency of the algorithm.
Computational results confirm the efficiency of the algorithm.
The results show the efficiency of the algorithm.
This may result in decreasing the efficiency of the algorithm.
Nonetheless, the efficiency of the algorithm is independent of the simulated temperature and not limited by the small-gap problem encountered in the Markov-Chain Monte Carlo algorithms.
The h-adaptive method is introduced to enhance the efficiency of the algorithm.
We test the efficiency of the algorithm with various smoothers and intergrid transfer operators.
Pruning the trees is shown to increase appreciably the efficiency of the algorithm.
Computational results are presented and the efficiency of the algorithm is discussed.
The performance and the efficiency of the algorithm are discussed, together with possible future improvements.
Several examples are presented to demonstrate the efficiency of the algorithm.
More suggestions(15)
the benefit of the algorithm
the benefits of the algorithm
the flow of the algorithm
the expectation of the algorithm
the distribution of the algorithm
the tolerance of the algorithm
the definition of the algorithm
the capability of the algorithm
the stability of the algorithm
the accuracy of the algorithm
the tyranny of the algorithm
the efficiency of the approach
the execution of the algorithm
the synoptic of the algorithm
the convergence of the algorithm
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