Results 11 to 20 of about 59,334 (307)
Grid Enabled Surrogate Modeling [PDF]
, 2009 The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling methods are often used for the efficient exploration of the design space, as they reduce the number of simulations needed.
Gorissen, Dirk +3 more
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IMPROVED PARTICLE SWARM OPTIMIZATION METHOD DIRECTED BY INDIRECT SURROGATE MODELING
Havacılık ve Uzay Teknolojileri Dergisi, 2015 An improved particle swarm optimization algorithm is proposed and tested for two different test cases: surface fitting of a wing shape and an inverse design of an airfoil in subsonic flow.
Yasin Volkan Pehlivanoğlu +2 more
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Surrogate Modeling of Nonlinear Dynamic Systems: A Comparative Study [PDF]
, 2022 Surrogate models play a vital role in overcoming the computational challenge in designing and analyzing nonlinear dynamic systems, especially in the presence of uncertainty.
Chen Jiang +9 more
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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
IEEE Access, 2020 Over the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures.
Anna Pietrenko-Dabrowska +2 more
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Two-stage variable-fidelity modeling of antennas with domain confinement
Scientific Reports, 2022 Surrogate modeling has become the method of choice in solving an increasing number of antenna design tasks, especially those involving expensive full-wave electromagnetic (EM) simulations. Notwithstanding, the curse of dimensionality considerably affects
Anna Pietrenko-Dabrowska +2 more
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Dynamical model of surrogate reactions [PDF]
Physical Review C, 2011 17 pages, 5 ...
Y. Aritomo, S. Chiba, K. Nishio
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Classical Surrogates for Quantum Learning Models
Physical Review Letters, 2023 The advent of noisy intermediate-scale quantum computers has put the search for possible applications to the forefront of quantum information science. One area where hopes for an advantage through near-term quantum computers are high is quantum machine learning, where variational quantum learning models based on parametrized quantum circuits are ...
Franz J. Schreiber +2 more
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IET Electric Power Applications, 2022 Electrical machine design optimization is an expensive procedure as it contains numerous variables and multiple objectives. Therefore, it might require hundreds of time‐consuming finite element analyses (FEA).
Farnam Farshbaf Roomi +2 more
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Kernel Methods for Surrogate Modeling
CoRR, 2019 This chapter deals with kernel methods as a special class of techniques for surrogate modeling. Kernel methods have proven to be efficient in machine learning, pattern recognition and signal analysis due to their flexibility, excellent experimental performance and elegant functional analytic background.
Santin G., Haasdonk B.
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Materials & Design, 2019 Inspired by gradient structures in the nature, Gradient Nanostructured (GNS) metals have emerged as a new class of materials with tunable microstructures.
Xin Chen, Haofei Zhou, Yumeng Li
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