Sentence examples for approximation we propose from inspiring English sources

Based on the first approximate and multi-step first approximation, we propose two formulas for the effectiveness factor expressed in general form and use them for an nth-order reaction.

Unlike earlier results employing a scenario approximation, we propose an offline sampling approach in the design phase instead of online scenario generation.

Thus, as a first-order approximation, we propose that the total nanofluid extinction coefficient is a simple addition of the base fluid extinction coefficient, σbasefluid, and that of the particles, σparticles.

To get better approximations, we propose four new linear mixed-integer programming models which can be combined with the existing approaches for modelling the booking period.

Based on the new approximations, we propose nonoscillatory spectral methods which possess the properties of both upwinding difference schemes and spectral methods.

Based on the successive approximation method, we propose an algorithm that jointly controls the rate and the persistent probability of the users.

To improve the approximation performance, we propose an iterative reweighted least-squares (IRLS) algorithm and demonstrate that with the filters designed by this algorithm, the approximation errors can be reduced.

With sample average approximation method, we propose stochastic distributed learning algorithms to help secondary users satisfy the constraints with the feedback information from primary links when maximizing the utilities.

Acknowledging the differing requirements posed by design (e.g., the convenience of an intuitive control net) and analysis (e.g., good approximation behavior), we propose the construction of a separate, smooth spline space for each while ensuring isogeometric compatibility – requiring the geometric models to be members of the analysis-suitable spaces.

The sparse approximation algorithm we propose ensures that the resulting sparse matrix still has all the properties relevant to its function in the Markov chain model.

Further, to obtain a better approximation we also propose a modification of these operators by using a King type approach.