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(accepted for publication)], we introduce a new and accurate method for approximation of the surface tension force.
In order to model the elliptical particles in the experiment, multi-sphere method was used, which is a suitable method for approximation of curved and smooth surface particles.
A fast method for approximation of Biot Savart type integrals over the tetrahedral elements is introduced, which uses an analytical expression for the nearest few elements, Gaussian quadratures for moderately distant elements, and a multipole expansion acceleration procedure for distant elements.
Such a method for approximation of fixed points is called the viscosity approximation method.
We now introduce the dual least squares method for approximation of the solutions of problem (1.1).
This iterative algorithm gives a method for approximation of a zero of a maximal monotone operator.
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We compute an extensive representation of the undistortion function as well as its statistics and use machine learning methods for approximation of the undistortion function.
There are several classical methods for approximation of solutions of nonlinear equation of one variable f ( x ) = 0 (1.1).
Moreover, iterative methods for approximation of fixed points of asymptotically nonexpansive mappings have been further studied by other authors (see, e.g., [16 18] and references therein).
One of the most popular methods for approximation of a minimizer of a convex function is the proximal point algorithm (PPA), which was introduced by Martinet [1] and Rockafellar [2] in Hilbert spaces.
A method for determination and two methods for approximation of the domain of attraction D a (0) of the asymptotically stable zero steady state of an autonomous, ℝ-analytical, discrete dynamical system are presented.
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