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Titlebook: Computational Science – ICCS 2024; 24th International C Leonardo Franco,Clélia de Mulatier,Peter M. A. Slo Conference proceedings 2024 The

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楼主: JOLT
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,The Seifert–Van Kampen Theorem,red by automatic differentiation (AD) alone. Although these estimators’ capability to guide a swift local search has been shown for certain problems, their applicability to models relevant to real-world applications remains largely unexplored. As the gradients governing the choice in candidate solut
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Leonardo Franco,Clélia de Mulatier,Peter M. A. Slo
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https://doi.org/10.1007/978-3-662-55350-3el iteratively. To enhance computational efficiency, we employ variable-resolution EM models. Tested on two microstrip circuits, our methodology competes effectively against several surrogate-based approaches. The average computational cost of the algorithm is below three hundred EM analyses of the
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Slices, Embeddings and Cancellation,logy leverages response feature technology, ensuring inherent regularization of the optimization task by exploring the nearly-linear dependence between the coordinates of feature points and the antenna‘s dimensions. The optimization process is structured as a machine learning (ML) procedure, utilizi
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General Cohomology Theory and Duality, HPO-5itr at 26 for full HPs; HPO-1itr at 13, HPO-5itr at 28 iterations for selected HPs), while HPO-static fails to approximate the minimum within the allocated 45 iterations for both scenarios. Mainly, HPO-5itr is the most balanced approach, found to require 21% of the time taken by HPO-1itr for t
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https://doi.org/10.1007/978-1-4684-9322-1th more accurately. This weighting scheme is combined with clustering methods based on a recursive matching algorithm. We evaluate and compare our approximation algorithm and recursive matching on several circuit instances and we obtain better results for a large number of instances with our algorit
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https://doi.org/10.1007/978-1-4612-4180-5algorithm, we solve the problem and find the optimal control structure and corresponding switching times. Lastly, we compare the results with results obtained using three popular optimisation modelling languages: Pyomo, AMPL and JuMP. These languages serve as interfaces for solving the optimal contr
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