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Different from current methods, our method can solve the problem.
In other words, constraint method can solve the following of each sensing node.
The proposed method can solve the first problem and can improve prediction stability.
Numerical tests show that simulation optimization method can solve the scheduling problem of container terminals efficiently.
The improved knife-edge method can solve the MTF value of images accurately and automatically to provide the focusing reference.
Additionally, this approximated method can solve various different differential equations such as integral, difference, integro-differential and functional differential equations.
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BFGS-WP can solve approximately 95% of the test problems, while the other methods can solve all the problems.
From the simulation results, we can see that the proposed methods can solve the problems mentioned above effectively.
Figure 4 indicates that BFGS-WP can solve approximately 93% of the test problems and that the other three methods can solve all the problems.
In contrast, the more general class of label correcting methods can solve anisotropic problems [3] and can sometimes be implemented on parallel computing architectures [37, 41].
One of the notable properties of GP is that new solution methods can solve even large-scale GPs extremely efficiently and reliably (Boyd et al. 2007).
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