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According to learning theory [ 26], minimizing 1 n w T (X T P X ) w corresponds to empirical risk minimization, whereas minimizing the objective in Eq. (10) corresponds to structural risk minimization that improves the generalizability of the resultant model.
We keep one of the two variables x, v fixed while minimizing the objective with respect to the other in an alternating fashion.
The membrane process design was optimized by minimizing the objective function; the overall processing cost.
A nonlinear global optimization scheme was applied to solve the Manning's coefficient through minimizing the objective function value.
Finally, the optimal values of decision variables are obtained by minimizing the objective function using a GA.
Finally, the optimal values of decision variables are obtained by minimizing the objective function using evolutionary genetic algorithm.
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The resulted bi-objective model is solved through goal programming method to minimizing the objectives, simultaneously.
The goal is to find k representative objects that minimize the objective function, which is the sum of the dissimilarities of all observations to their closest medoid.
The optimization algorithm used to minimize the objective function and damage detection procedures are explained.
A simulated annealing and particle swarm optimization algorithm are separately applied to minimize the objective function.
GSAs are employed to minimize the objective functions in the appropriately defined optimization problems.
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