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For both models, the optimization problem is to minimize the total incurred cost under a constraint on the outgoing quality.
By using fully parameterized models, the optimization approach is adaptable to other scaffold designs and bone defect situations.
For structural models, the optimization (relaxation) of the geometry (finding the equilibrium of ions coordinates, in which the full electronic energy of the system is minimal) was carried.
The algorithm is based on an approach that models the optimization problem into a directed acyclic graph and then addresses the complex optimization problem step by step.
For the two models the optimization algorithm found 21,968 (loss-of-signal) and 23,121 (interference) valid parameter sets.
While the performance on an external test set should be used to compare different models, the optimization performance is suited to compare the capability of the evolutionary algorithms to find the optimum of a given problem.
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Of the full mixed-effects models, the optimization-based approach resulted in the best simulation results according to all criteria (Table 6, Figure 6).
Through this optimization model, the optimization objectives of both microgrid operational modes can be combined.
In the standard C-SVM model, the optimization problem is transformed into a duality problem.
We model the optimization problem using a stationary infinite-horizon MDP.
We model the optimization problem using a stationary infinite-horizon Markov decision process (MDP).
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