Sentence examples for modified penalty from inspiring English sources

To investigate the effectiveness of the proposed modification, we compare the performance of BRGA under both the original and the modified penalty functions.

h(k) is a dynamically modified penalty value, k is the algorithm's current iteration number; S is the feasible set and H x) is a penalty factor, which is always problem dependent.

With the introduced modifications in the residual monitored for convergence, the modified penalty method is able to significantly exploit matrix re-use, and substantially improve its computational efficiency.

Similarly to the modifications introduced in the weakly penalized approach, in the modified penalty formulation we measure the convergence of ‖ R + R P ∗ ‖ instead of ‖ R + R P ‖.

A modified penalty for an honest report isn't despotic, it's just plain screwy.

We have introduced a modified penalty approach into the flow-structure interaction solver that combines an immersed boundary method (IBM) and a multi-block lattice Boltzmann method (LBM) to model an incompressible flow and elastic boundaries with finite mass.

In this paper, a modified exact penalty function for equality constrained nonlinear programming problem is constructed by augmenting a new variable that controls the constraint violence.

Iterative convergence of the radiation equation is accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.

In this paper, a modified simple penalty function is proposed for a constrained nonlinear programming problem by augmenting the dimension of the program with a variable that controls the weight of the penalty terms.

Also tandem mismatches represent a special motif of MM-probes with a modified intensity penalty compared with other MM-probes possessing two mismatches with at least one WC pairing in-between.

To further balance our model to make it equally good at identifying men and women, we tried either modifying the penalty term for each gender (inversely proportional to its relative frequency in the training set) or creating a balanced train set by undersampling the majority class while retaining the original population distribution in the test set.