Artículos de revistas sobre el tema "Multi-fidelity models"
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Razi, Mani, Robert M. Kirby y Akil Narayan. "Fast predictive multi-fidelity prediction with models of quantized fidelity levels". Journal of Computational Physics 376 (enero de 2019): 992–1008. http://dx.doi.org/10.1016/j.jcp.2018.10.025.
Texto completoPerdikaris, P., M. Raissi, A. Damianou, N. D. Lawrence y G. E. Karniadakis. "Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling". Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, n.º 2198 (febrero de 2017): 20160751. http://dx.doi.org/10.1098/rspa.2016.0751.
Texto completoRumpfkeil, Markus P., Dean Bryson y Phil Beran. "Multi-Fidelity Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Analytical Benchmark Problems". Algorithms 15, n.º 3 (21 de marzo de 2022): 101. http://dx.doi.org/10.3390/a15030101.
Texto completoDiazDelaO, F. A. y S. Adhikari. "Bayesian assimilation of multi-fidelity finite element models". Computers & Structures 92-93 (febrero de 2012): 206–15. http://dx.doi.org/10.1016/j.compstruc.2011.11.002.
Texto completoRumpfkeil, Markus P. y Philip Beran. "Multi-fidelity surrogate models for flutter database generation". Computers & Fluids 197 (enero de 2020): 104372. http://dx.doi.org/10.1016/j.compfluid.2019.104372.
Texto completoBonomo, Anthony L. "Multi-fidelity surrogate modeling for structural acoustics applications". Journal of the Acoustical Society of America 153, n.º 3_supplement (1 de marzo de 2023): A287. http://dx.doi.org/10.1121/10.0018869.
Texto completoPeart, Tanya, Nicolas Aubin, Stefano Nava, John Cater y Stuart Norris. "Selection of Existing Sail Designs for Multi-Fidelity Surrogate Models". Journal of Sailing Technology 7, n.º 01 (5 de enero de 2022): 31–51. http://dx.doi.org/10.5957/jst/2022.7.2.31.
Texto completoPeart, Tanya, Nicolas Aubin, Stefano Nava, John Cater y Stuart Norris. "Multi-Fidelity Surrogate Models for VPP Aerodynamic Input Data". Journal of Sailing Technology 6, n.º 01 (9 de febrero de 2021): 21–43. http://dx.doi.org/10.5957/jst/2021.6.1.21.
Texto completoFarcaș, Ionuț-Gabriel, Benjamin Peherstorfer, Tobias Neckel, Frank Jenko y Hans-Joachim Bungartz. "Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification". Computer Methods in Applied Mechanics and Engineering 406 (marzo de 2023): 115908. http://dx.doi.org/10.1016/j.cma.2023.115908.
Texto completoStyler, Breelyn y Reid Simmons. "Plan-Time Multi-Model Switching for Motion Planning". Proceedings of the International Conference on Automated Planning and Scheduling 27 (5 de junio de 2017): 558–66. http://dx.doi.org/10.1609/icaps.v27i1.13858.
Texto completoYi, Jin, Yichi Shen y Christine A. Shoemaker. "A multi-fidelity RBF surrogate-based optimization framework for computationally expensive multi-modal problems with application to capacity planning of manufacturing systems". Structural and Multidisciplinary Optimization 62, n.º 4 (17 de mayo de 2020): 1787–807. http://dx.doi.org/10.1007/s00158-020-02575-7.
Texto completoSun, Qi, Tinghuan Chen, Siting Liu, Jianli Chen, Hao Yu y Bei Yu. "Correlated Multi-objective Multi-fidelity Optimization for HLS Directives Design". ACM Transactions on Design Automation of Electronic Systems 27, n.º 4 (31 de julio de 2022): 1–27. http://dx.doi.org/10.1145/3503540.
Texto completoYoo, Kwangkyu, Omar Bacarreza y M. H. Ferri Aliabadi. "Multi-fidelity robust design optimisation for composite structures based on low-fidelity models using successive high-fidelity corrections". Composite Structures 259 (marzo de 2021): 113477. http://dx.doi.org/10.1016/j.compstruct.2020.113477.
Texto completoSong, Xueguan, Liye Lv, Wei Sun y Jie Zhang. "A radial basis function-based multi-fidelity surrogate model: exploring correlation between high-fidelity and low-fidelity models". Structural and Multidisciplinary Optimization 60, n.º 3 (1 de abril de 2019): 965–81. http://dx.doi.org/10.1007/s00158-019-02248-0.
Texto completoLiu, Bo, Slawomir Koziel y Nazar Ali. "SADEA-II: A generalized method for efficient global optimization of antenna design". Journal of Computational Design and Engineering 4, n.º 2 (20 de noviembre de 2016): 86–97. http://dx.doi.org/10.1016/j.jcde.2016.11.002.
Texto completoGalindo, José, Roberto Navarro, Francisco Moya y Andrea Conchado. "Comprehensive Method for Obtaining Multi-Fidelity Surrogate Models for Design Space Approximation: Application to Multi-Dimensional Simulations of Condensation Due to Mixing Streams". Applied Sciences 13, n.º 11 (23 de mayo de 2023): 6361. http://dx.doi.org/10.3390/app13116361.
Texto completoYounis, Adel y Zuomin Dong. "High-Fidelity Surrogate Based Multi-Objective Optimization Algorithm". Algorithms 15, n.º 8 (7 de agosto de 2022): 279. http://dx.doi.org/10.3390/a15080279.
Texto completoBaldan, Marco, Alexander Nikanorov y Bernard Nacke. "A parallel multi-fidelity optimization approach in induction hardening". COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 39, n.º 1 (27 de noviembre de 2019): 133–43. http://dx.doi.org/10.1108/compel-05-2019-0221.
Texto completoGurbuz, Caglar, Martin Eser, Johannes Schaffner y Steffen Marburg. "A multi-fidelity Gaussian process for efficient frequency sweeps in the acoustic design of a vehicle cabin". Journal of the Acoustical Society of America 153, n.º 4 (abril de 2023): 2006–18. http://dx.doi.org/10.1121/10.0017725.
Texto completoLeguizamo, David Felipe, Hsin-Jung Yang, Xian Yeow Lee y Soumik Sarkar. "Deep Reinforcement Learning for Robotic Control with Multi-Fidelity Models". IFAC-PapersOnLine 55, n.º 37 (2022): 193–98. http://dx.doi.org/10.1016/j.ifacol.2022.11.183.
Texto completoPerron, Christian, Dushhyanth Rajaram y Dimitri N. Mavris. "Multi-fidelity non-intrusive reduced-order modelling based on manifold alignment". Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 477, n.º 2253 (septiembre de 2021): 20210495. http://dx.doi.org/10.1098/rspa.2021.0495.
Texto completoLi, Yang, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang y Bin Cui. "MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 10 (18 de mayo de 2021): 8491–500. http://dx.doi.org/10.1609/aaai.v35i10.17031.
Texto completoBonfiglio, Luca, Paris Perdikaris y Stefano Brizzolara. "Multi-fidelity Bayesian Optimization of SWATH Hull Forms". Journal of Ship Research 64, n.º 02 (1 de junio de 2020): 154–70. http://dx.doi.org/10.5957/jsr.2020.64.2.154.
Texto completoLeifsson, Leifur y Slawomir Koziel. "Adaptive response prediction for aerodynamic shape optimization". Engineering Computations 34, n.º 5 (3 de julio de 2017): 1485–500. http://dx.doi.org/10.1108/ec-02-2016-0070.
Texto completoKonrad, Julia, Ionuţ-Gabriel Farcaş, Benjamin Peherstorfer, Alessandro Di Siena, Frank Jenko, Tobias Neckel y Hans-Joachim Bungartz. "Data-driven low-fidelity models for multi-fidelity Monte Carlo sampling in plasma micro-turbulence analysis". Journal of Computational Physics 451 (febrero de 2022): 110898. http://dx.doi.org/10.1016/j.jcp.2021.110898.
Texto completoBaldo, Leonardo, Pier Carlo Berri, Matteo D. L. Dalla Vedova y Paolo Maggiore. "Experimental Validation of Multi-fidelity Models for Prognostics of Electromechanical Actuators". PHM Society European Conference 7, n.º 1 (29 de junio de 2022): 32–42. http://dx.doi.org/10.36001/phme.2022.v7i1.3347.
Texto completoMorse, Llewellyn, Zahra Sharif Khodaei y M. H. Aliabadi. "Multi-Fidelity Modeling-Based Structural Reliability Analysis with the Boundary Element Method". Journal of Multiscale Modelling 08, n.º 03n04 (septiembre de 2017): 1740001. http://dx.doi.org/10.1142/s1756973717400017.
Texto completoAmrit, Anand y Leifur Leifsson. "Applications of surrogate-assisted and multi-fidelity multi-objective optimization algorithms to simulation-based aerodynamic design". Engineering Computations 37, n.º 2 (9 de agosto de 2019): 430–57. http://dx.doi.org/10.1108/ec-12-2018-0553.
Texto completoLin, James T., Chun-Chih Chiu, Edward Huang y Hung-Ming Chen. "A Multi-Fidelity Model Approach for Simultaneous Scheduling of Machines and Vehicles in Flexible Manufacturing Systems". Asia-Pacific Journal of Operational Research 35, n.º 01 (febrero de 2018): 1850005. http://dx.doi.org/10.1142/s0217595918500057.
Texto completoFu, Wenbo, Qiushi Li, Yongshun Song, Yaogen Shu, Zhongcan Ouyang y Ming Li. "Theoretical analysis of RNA polymerase fidelity: a steady-state copolymerization approach". Communications in Theoretical Physics 74, n.º 1 (10 de diciembre de 2021): 015601. http://dx.doi.org/10.1088/1572-9494/ac3993.
Texto completoKoziel, Slawomir, Yonatan Tesfahunegn y Leifur Leifsson. "Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization". Engineering Computations 33, n.º 8 (7 de noviembre de 2016): 2320–38. http://dx.doi.org/10.1108/ec-09-2015-0277.
Texto completoEllison, M., F. A. DiazDelaO, N. Z. Ince y M. Willetts. "Robust optimisation of computationally expensive models using adaptive multi-fidelity emulation". Applied Mathematical Modelling 100 (diciembre de 2021): 92–106. http://dx.doi.org/10.1016/j.apm.2021.07.020.
Texto completoSONG, Chao, Xudong YANG y Wenping SONG. "Multi-infill strategy for kriging models used in variable fidelity optimization". Chinese Journal of Aeronautics 31, n.º 3 (marzo de 2018): 448–56. http://dx.doi.org/10.1016/j.cja.2018.01.011.
Texto completoPilania, G., J. E. Gubernatis y T. Lookman. "Multi-fidelity machine learning models for accurate bandgap predictions of solids". Computational Materials Science 129 (marzo de 2017): 156–63. http://dx.doi.org/10.1016/j.commatsci.2016.12.004.
Texto completoDu, Wenting y Jin Su. "Uncertainty Quantification for Numerical Solutions of the Nonlinear Partial Differential Equations by Using the Multi-Fidelity Monte Carlo Method". Applied Sciences 12, n.º 14 (12 de julio de 2022): 7045. http://dx.doi.org/10.3390/app12147045.
Texto completoXu, Jie, Si Zhang, Edward Huang, Chun-Hung Chen, Loo Hay Lee y Nurcin Celik. "MO2TOS: Multi-Fidelity Optimization with Ordinal Transformation and Optimal Sampling". Asia-Pacific Journal of Operational Research 33, n.º 03 (junio de 2016): 1650017. http://dx.doi.org/10.1142/s0217595916500172.
Texto completoAvramova, Maria, Agustin Abarca, Jason Hou y Kostadin Ivanov. "Innovations in Multi-Physics Methods Development, Validation, and Uncertainty Quantification". Journal of Nuclear Engineering 2, n.º 1 (7 de marzo de 2021): 44–56. http://dx.doi.org/10.3390/jne2010005.
Texto completoKlimczyk, Witold Artur y Zdobyslaw Jan Goraj. "Analysis and optimization of morphing wing aerodynamics". Aircraft Engineering and Aerospace Technology 91, n.º 3 (4 de marzo de 2019): 538–46. http://dx.doi.org/10.1108/aeat-12-2017-0289.
Texto completoDeng, Xinjian, Enying Li y Hu Wang. "A Variable-Fidelity Multi-Objective Evolutionary Method for Polygonal Pin Fin Heat Sink Design". Sustainability 15, n.º 2 (6 de enero de 2023): 1104. http://dx.doi.org/10.3390/su15021104.
Texto completoHe, Lei, Weiqi Qian, Tun Zhao y Qing Wang. "Multi-Fidelity Aerodynamic Data Fusion with a Deep Neural Network Modeling Method". Entropy 22, n.º 9 (12 de septiembre de 2020): 1022. http://dx.doi.org/10.3390/e22091022.
Texto completoYang, Chih-Hsuan, Balaji Sesha Sarath Pokuri, Xian Yeow Lee, Sangeeth Balakrishnan, Chinmay Hegde, Soumik Sarkar y Baskar Ganapathysubramanian. "Multi-fidelity machine learning models for structure–property mapping of organic electronics". Computational Materials Science 213 (octubre de 2022): 111599. http://dx.doi.org/10.1016/j.commatsci.2022.111599.
Texto completoZhang, Chi, Chaolin Song y Abdollah Shafieezadeh. "Adaptive reliability analysis for multi-fidelity models using a collective learning strategy". Structural Safety 94 (enero de 2022): 102141. http://dx.doi.org/10.1016/j.strusafe.2021.102141.
Texto completoKoziel, Slawomir y Stanislav Ogurtsov. "Multi-Objective Design of Antennas Using Variable-Fidelity Simulations and Surrogate Models". IEEE Transactions on Antennas and Propagation 61, n.º 12 (diciembre de 2013): 5931–39. http://dx.doi.org/10.1109/tap.2013.2283599.
Texto completoThandayutham, Karthikeyan y Abdus Samad. "Hydrostructural Optimization of a Marine Current Turbine Through Multi-fidelity Numerical Models". Arabian Journal for Science and Engineering 45, n.º 2 (8 de octubre de 2019): 935–52. http://dx.doi.org/10.1007/s13369-019-04185-y.
Texto completoYang, Yibo y Paris Perdikaris. "Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems". Computational Mechanics 64, n.º 2 (21 de mayo de 2019): 417–34. http://dx.doi.org/10.1007/s00466-019-01718-y.
Texto completoEaton, Ammon N., Logan D. R. Beal, Samuel D. Thorpe, Casey B. Hubbell, John D. Hedengren, Roar Nybø y Manuel Aghito. "Real time model identification using multi-fidelity models in managed pressure drilling". Computers & Chemical Engineering 97 (febrero de 2017): 76–84. http://dx.doi.org/10.1016/j.compchemeng.2016.11.008.
Texto completoGuo, Qi, Jiutao Hang, Suian Wang, Wenzhi Hui y Zonghong Xie. "Design optimization of variable stiffness composites by using multi-fidelity surrogate models". Structural and Multidisciplinary Optimization 63, n.º 1 (23 de julio de 2020): 439–61. http://dx.doi.org/10.1007/s00158-020-02684-3.
Texto completoBabaee, H., P. Perdikaris, C. Chryssostomidis y G. E. Karniadakis. "Multi-fidelity modelling of mixed convection based on experimental correlations and numerical simulations". Journal of Fluid Mechanics 809 (21 de noviembre de 2016): 895–917. http://dx.doi.org/10.1017/jfm.2016.718.
Texto completoQuattrocchi, Gaetano, Matteo D. L. Dalla Vedova y Pier Carlo Berri. "Lumped parameters multi-fidelity digital twins for prognostics of electromechanical actuators". Journal of Physics: Conference Series 2526, n.º 1 (1 de junio de 2023): 012076. http://dx.doi.org/10.1088/1742-6596/2526/1/012076.
Texto completoLiu, H., M. Hou, A. Li y L. Xie. "AN AUTOMATIC EXTRACTION METHOD FOR THE PARAMETERS OF MULTI-LOD BIM MODELS FOR TYPICAL COMPONENTS OF WOODEN ARCHITECTURAL HERITAGE". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (23 de agosto de 2019): 679–85. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-679-2019.
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