Sentence examples for loss maximization from inspiring English sources

To improve qualified product yield with low energy consumption, in this paper, multi-objective optimization of various conflicting objectives (namely minimization of combustion loss, maximization of TA yield) is conducted using self-adaptive multi-objective differential evolution algorithm (SADE).

The results indicate that higher HC level can be achieved using the proposed filter design approach compared to three conventional filter design approaches as voltage total harmonic distortion minimization, line loss minimization and power factor maximization.

GA optimizes a given fitness function whose objectives are the loss minimization and the voltage stability margin maximization.

In this field, the most common approaches solve this problem based on the minimization of a quadratic loss function or the maximization of a probability distribution.

The hallmark of Graham's value investing approach is not so much profit maximization but loss minimization.

Reduction in the percentage variation of static pressure at impeller outlet, minimization of losses inside volute and maximization of stagnation pressure at volute outlet are selected as quality characteristics to ensure the enhancement of centrifugal blower performance.

How is the principle of value maximization (minimizing losses) played out in Sophie's Choice?

The subproblem is aiming to find the worst case under attack with given reinforcement plan, which is the maximization of economic loss for load curtailment.

The behavioural model represents utility maximization under myopic loss aversion (MLA) within an ultimatum game (UG) framework where the two players are the EV-owner and the electricity supplier.

Constrained optimization is conducted for maximization of modal loss factors and minimization of weight of sandwich beams and plates with elastic laminated constraining layers and a viscoelastic core, with layer thickness and material and laminate layer ply orientation angles as design variables.

This procedure is based on the maximization of the insertion loss of candidate profiles proposed by an evolutionary algorithm.