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This system of characteristic functions can be used as a complete set to express the solution over the non-uniform region, so that the numerical problem to be solved is of a much lower dimension than that yielded by conventional numerical methods.
Estimates are produced by conventional numerical methods.
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Together, these allow us to characterize particular behaviors of interest by performing detailed and focused analyses with conventional numerical methods.
Because of its non-local character, the model described by (1), or its extension (61), is challenging to solve with conventional numerical methods.
Although there are conventional numerical methods like finite difference method and finite volume method for forecast of morphological change by solving flow and morphodynamic equations, the methods are too complex/inefficient to be applied to a real large scale problem.
Conventional numerical methods for finding multiple roots of polynomials are inaccurate.
Accurate numerical simulation of such systems is a challenging task using conventional numerical methods.
Data-driven techniques can be classified into conventional numerical methods and machine learning methods Fig. 12.
Therefore, solving (10) can be approached via conventional numerical methods [36], though at the price of a high computational load.
Figure 12 Comparison of the results for mean polariton number in the central cavity obtained by the P -function mean-field method, red line, and by the conventional numerical method, dashed lines, with cut-offs at three (black), four (blue) and five (green) excitations.
Since the fuzzy market demands and inventory costs usually have infinite supports, the proposed two-stage fuzzy MPMP production planning problem is an infinite-dimensional optimization problem that cannot be solved directly by conventional numerical solution methods.
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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.
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