Sentence examples for behavior of the exact from inspiring English sources

Numerical methods for solving the flow equations in cylindrical or spherical coordinates should be able to capture the behavior of the exact solution near the regions where the particular form of the governing equations is singular.

The classical explanation for this phenomenon investigates the behavior of the exact solution to the numerical method in combination with the finite error terms, often referred to as the modified equation.

With the aid of the long-term behavior of the exact solution, the steady motions of the oscillator with 0, 1, 2, 4, 6, 8, 10, 12, 14 stops per cycle are categorized in the parametric space of the ratios of forces and frequencies.

For constructing layer-adapted meshes correctly, we need to know the asymptotic behavior of the exact solution.

This behavior of the exact motivates researchers to focus on heuristic and metaheuristic approaches to find optimal or near optimal solution.

In Figures 1-3, the behavior of the exact solution and the numerical solution of the fractional wave equation (2) by means of the fractional finite difference method based on the Hermite formula with different values of α, Δx, Δt and the final time T is given.

Thus, a fracture test using a pipe specimen of real scale needs to be carried out to obtain accurate fracture behavior for the exact integrity evaluation of a piping system.

Furthermore, the inherent difficulty of this problem when dealing with the original real-valued expression matrix and the great interest in finding coherent behaviors regardless of the exact numeric values in the matrix, has led many authors to a formulation based on a discretized version of the expression matrix [ 7- 9, 12- 23].

This behavior is independent of the exact number of unmixed individuals in the dataset and can be observed for both ADMIXTURE and EIGENSOFT.

b We use the approximate expression 4M log(M −6M+8 as a first approximation and to better appreciate the behavior of the complexity; however, the exact calculation of the number of flops for IFFT is given [27] by (frac {34}{9} M log (M) - frac {124}{27} M -2 log (M) + frac {16}{27} (-1)^{log (M } (1 - 3/8 log (M)) +8).

In order to have a closer look at the different behavior of the approximate and the exact CRLB, the normalized difference between the symbol-rate sampled and the oversampled CRLB according to CRLB J = 1 − CRLB J = 2 CRLB J = 1, (45). is plotted for each type in Figure4b.