Artículos de revistas sobre el tema "Data-driven model order reduction"
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Nagy, Peter y Marco Fossati. "Adaptive Data-Driven Model Order Reduction for Unsteady Aerodynamics". Fluids 7, n.º 4 (6 de abril de 2022): 130. http://dx.doi.org/10.3390/fluids7040130.
Texto completoGosea, Ion Victor y Athanasios C. Antoulas. "Data-driven model order reduction of quadratic-bilinear systems". Numerical Linear Algebra with Applications 25, n.º 6 (22 de julio de 2018): e2200. http://dx.doi.org/10.1002/nla.2200.
Texto completoShah, Aarohi y Julian J. Rimoli. "Smart parts: Data-driven model order reduction for nonlinear mechanical assemblies". Finite Elements in Analysis and Design 200 (marzo de 2022): 103682. http://dx.doi.org/10.1016/j.finel.2021.103682.
Texto completoSarna, Neeraj y Peter Benner. "Data-Driven model order reduction for problems with parameter-dependent jump-discontinuities". Computer Methods in Applied Mechanics and Engineering 387 (diciembre de 2021): 114168. http://dx.doi.org/10.1016/j.cma.2021.114168.
Texto completoPierquin, A., T. Henneron y S. Clenet. "Data-Driven Model-Order Reduction for Magnetostatic Problem Coupled With Circuit Equations". IEEE Transactions on Magnetics 54, n.º 3 (marzo de 2018): 1–4. http://dx.doi.org/10.1109/tmag.2017.2771358.
Texto completoPeng, Haijun, Ningning Song y Ziyun Kan. "Data-driven model order reduction with proper symplectic decomposition for flexible multibody system". Nonlinear Dynamics 107, n.º 1 (6 de noviembre de 2021): 173–203. http://dx.doi.org/10.1007/s11071-021-06990-3.
Texto completoKim, Hyejin, Haeseong Cho, Sihun Lee, SangJoon Shin y Haedeong Kim. "Development of an Efficient Nonlinear Structural Analysis Using Data-driven Model Order Reduction". Transactions of the Korean Society for Noise and Vibration Engineering 31, n.º 6 (20 de diciembre de 2021): 604–13. http://dx.doi.org/10.5050/ksnve.2021.31.6.604.
Texto completoGosea, I. V., M. Petreczky y A. C. Antoulas. "Data-Driven Model Order Reduction of Linear Switched Systems in the Loewner Framework". SIAM Journal on Scientific Computing 40, n.º 2 (enero de 2018): B572—B610. http://dx.doi.org/10.1137/17m1120233.
Texto completoSpinosa, Angelo Giuseppe, Arturo Buscarino, Luigi Fortuna, Matteo Iafrati y Giuseppe Mazzitelli. "Data-driven order reduction in Hammerstein–Wiener models of plasma dynamics". Engineering Applications of Artificial Intelligence 100 (abril de 2021): 104180. http://dx.doi.org/10.1016/j.engappai.2021.104180.
Texto completoCasciati, Fabio y Lucia Faravelli. "Sensor placement driven by a model order reduction (MOR) reasoning". Smart Structures and Systems 13, n.º 3 (25 de marzo de 2014): 343–52. http://dx.doi.org/10.12989/sss.2014.13.3.343.
Texto completoZhang, Yi, Yi-Fei Pu, Jin-Rong Hu, Yan Liu, Qing-Li Chen y Ji-Liu Zhou. "Efficient CT Metal Artifact Reduction Based on Fractional-Order Curvature Diffusion". Computational and Mathematical Methods in Medicine 2011 (2011): 1–9. http://dx.doi.org/10.1155/2011/173748.
Texto completoBuchfink, Patrick, Ashish Bhatt y Bernard Haasdonk. "Symplectic Model Order Reduction with Non-Orthonormal Bases". Mathematical and Computational Applications 24, n.º 2 (21 de abril de 2019): 43. http://dx.doi.org/10.3390/mca24020043.
Texto completoLuo, Yushuang, Xiantao Li y Wenrui Hao. "Stability preserving data-driven models with latent dynamics". Chaos: An Interdisciplinary Journal of Nonlinear Science 32, n.º 8 (agosto de 2022): 081103. http://dx.doi.org/10.1063/5.0096889.
Texto completoLi, Yong, Jue Yang, Wei Long Liu y Cheng Lin Liao. "Multi-Level Model Reduction and Data-Driven Identification of the Lithium-Ion Battery". Energies 13, n.º 15 (23 de julio de 2020): 3791. http://dx.doi.org/10.3390/en13153791.
Texto completoDeshmukh, Rohit, Jack J. McNamara, Zongxian Liang, J. Zico Kolter y Abhijit Gogulapati. "Model order reduction using sparse coding exemplified for the lid-driven cavity". Journal of Fluid Mechanics 808 (27 de octubre de 2016): 189–223. http://dx.doi.org/10.1017/jfm.2016.616.
Texto completoSong, Ningning, Haijun Peng y Ziyun Kan. "A hybrid data-driven model order reduction strategy for flexible multibody systems considering impact and friction". Mechanism and Machine Theory 169 (marzo de 2022): 104649. http://dx.doi.org/10.1016/j.mechmachtheory.2021.104649.
Texto completoBao, Anqi, Eduardo Gildin, Abhinav Narasingam y Joseph S. Kwon. "Data-Driven Model Reduction for Coupled Flow and Geomechanics Based on DMD Methods". Fluids 4, n.º 3 (19 de julio de 2019): 138. http://dx.doi.org/10.3390/fluids4030138.
Texto completoIbañez, R., E. Abisset-Chavanne, E. Cueto, A. Ammar, J. L. Duval y F. Chinesta. "Some applications of compressed sensing in computational mechanics: model order reduction, manifold learning, data-driven applications and nonlinear dimensionality reduction". Computational Mechanics 64, n.º 5 (10 de abril de 2019): 1259–71. http://dx.doi.org/10.1007/s00466-019-01703-5.
Texto completoGerman, Péter, Mauricio E. Tano, Carlo Fiorina y Jean C. Ragusa. "Data-Driven Reduced-Order Modeling of Convective Heat Transfer in Porous Media". Fluids 6, n.º 8 (28 de julio de 2021): 266. http://dx.doi.org/10.3390/fluids6080266.
Texto completoMendonça, Gonçalo, Frederico Afonso y Fernando Lau. "Model order reduction in aerodynamics: Review and applications". Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, n.º 15 (11 de junio de 2019): 5816–36. http://dx.doi.org/10.1177/0954410019853472.
Texto completoTaddei, Tommaso. "A Registration Method for Model Order Reduction: Data Compression and Geometry Reduction". SIAM Journal on Scientific Computing 42, n.º 2 (enero de 2020): A997—A1027. http://dx.doi.org/10.1137/19m1271270.
Texto completoMorsy, Ahmed Amr, Mariella Kast y Paolo Tiso. "A frequency-domain reduced order model for joints by hyper-reduction and model-driven sampling". Mechanical Systems and Signal Processing 185 (febrero de 2023): 109744. http://dx.doi.org/10.1016/j.ymssp.2022.109744.
Texto completoAkram, Namra, Mehboob Alam, Rashida Hussain, Asghar Ali, Shah Muhammad, Rahila Malik y Anwar Ul Haq. "Passivity Preserving Model Order Reduction Using the Reduce Norm Method". Electronics 9, n.º 6 (9 de junio de 2020): 964. http://dx.doi.org/10.3390/electronics9060964.
Texto completoXie, Xuping, Guannan Zhang y Clayton G. Webster. "Non-Intrusive Inference Reduced Order Model for Fluids Using Deep Multistep Neural Network". Mathematics 7, n.º 8 (19 de agosto de 2019): 757. http://dx.doi.org/10.3390/math7080757.
Texto completoDemo, Nicola, Marco Tezzele, Andrea Mola y Gianluigi Rozza. "Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing". Journal of Marine Science and Engineering 9, n.º 2 (11 de febrero de 2021): 185. http://dx.doi.org/10.3390/jmse9020185.
Texto completoBittner, Brian, Ross L. Hatton y Shai Revzen. "Data-driven geometric system identification for shape-underactuated dissipative systems". Bioinspiration & Biomimetics 17, n.º 2 (24 de enero de 2022): 026004. http://dx.doi.org/10.1088/1748-3190/ac3b9c.
Texto completoZhong, Jiaqi y Shan Liang. "A Data-Driven Based Spatiotemporal Model Reduction for Microwave Heating Process with the Mixed Boundary Conditions". Processes 9, n.º 5 (9 de mayo de 2021): 827. http://dx.doi.org/10.3390/pr9050827.
Texto completoBoubehziz, Toufik, Carlos Quesada-Granja, Claire Dupont, Pierre Villon, Florian De Vuyst y Anne-Virginie Salsac. "A Data-Driven Space-Time-Parameter Reduced-Order Model with Manifold Learning for Coupled Problems: Application to Deformable Capsules Flowing in Microchannels". Entropy 23, n.º 9 (9 de septiembre de 2021): 1193. http://dx.doi.org/10.3390/e23091193.
Texto completoHou, Hui, Hao Geng, Yong Huang, Hao Wu, Xixiu Wu y Shiwen Yu. "Damage Probability Assessment of Transmission Line-Tower System Under Typhoon Disaster, Based on Model-Driven and Data-Driven Views". Energies 12, n.º 8 (16 de abril de 2019): 1447. http://dx.doi.org/10.3390/en12081447.
Texto completoRahman, Sk, Omer San y Adil Rasheed. "A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence". Fluids 3, n.º 4 (31 de octubre de 2018): 86. http://dx.doi.org/10.3390/fluids3040086.
Texto completoLi, Zhengyuan, Jie Chen, Yanmei Meng, Jihong Zhu, Jiqin Li, Yue Zhang y Chengfeng Li. "Multi-Objective Optimization of Sugarcane Milling System Operations Based on a Deep Data-Driven Model". Foods 11, n.º 23 (28 de noviembre de 2022): 3845. http://dx.doi.org/10.3390/foods11233845.
Texto completoSengupta, P. y S. Chakraborty. "Model reduction technique for Bayesian model updating of structural parameters using simulated modal data". Proceedings of the 12th Structural Engineering Convention, SEC 2022: Themes 1-2 1, n.º 1 (19 de diciembre de 2022): 1403–12. http://dx.doi.org/10.38208/acp.v1.670.
Texto completoSledge, Isaac y José Príncipe. "Reduction of Markov Chains Using a Value-of-Information-Based Approach". Entropy 21, n.º 4 (30 de marzo de 2019): 349. http://dx.doi.org/10.3390/e21040349.
Texto completoLu, Xiaoxin, Julien Yvonnet, Leonidas Papadopoulos, Ioannis Kalogeris y Vissarion Papadopoulos. "A Stochastic FE2 Data-Driven Method for Nonlinear Multiscale Modeling". Materials 14, n.º 11 (27 de mayo de 2021): 2875. http://dx.doi.org/10.3390/ma14112875.
Texto completoCsala, Hunor, Scott T. M. Dawson y Amirhossein Arzani. "Comparing different nonlinear dimensionality reduction techniques for data-driven unsteady fluid flow modeling". Physics of Fluids 34, n.º 11 (noviembre de 2022): 117119. http://dx.doi.org/10.1063/5.0127284.
Texto completoLoiseau, Jean-Christophe y Steven L. Brunton. "Constrained sparse Galerkin regression". Journal of Fluid Mechanics 838 (10 de enero de 2018): 42–67. http://dx.doi.org/10.1017/jfm.2017.823.
Texto completoChamorro, Harold R., Alvaro D. Orjuela-Cañón, David Ganger, Mattias Persson, Francisco Gonzalez-Longatt, Lazaro Alvarado-Barrios, Vijay K. Sood y Wilmar Martinez. "Data-Driven Trajectory Prediction of Grid Power Frequency Based on Neural Models". Electronics 10, n.º 2 (12 de enero de 2021): 151. http://dx.doi.org/10.3390/electronics10020151.
Texto completoLučin, Ivana, Bože Lučin, Zoran Čarija y Ante Sikirica. "Data-Driven Leak Localization in Urban Water Distribution Networks Using Big Data for Random Forest Classifier". Mathematics 9, n.º 6 (22 de marzo de 2021): 672. http://dx.doi.org/10.3390/math9060672.
Texto completoRubio, P.-B., F. Louf y L. Chamoin. "Bayesian data assimilation with Transport Map sampling and PGD model order reduction". Journal of Physics: Conference Series 1476 (marzo de 2020): 012004. http://dx.doi.org/10.1088/1742-6596/1476/1/012004.
Texto completoGonzález, David, Alberto Badías, Icíar Alfaro, Francisco Chinesta y Elías Cueto. "Model order reduction for real-time data assimilation through Extended Kalman Filters". Computer Methods in Applied Mechanics and Engineering 326 (noviembre de 2017): 679–93. http://dx.doi.org/10.1016/j.cma.2017.08.041.
Texto completoStefanoiu, Dan y Janetta Culita. "Joint Stochastic Spline and Autoregressive Identification Aiming Order Reduction Based on Noisy Sensor Data". Sensors 20, n.º 18 (4 de septiembre de 2020): 5038. http://dx.doi.org/10.3390/s20185038.
Texto completoDaescu, D. N. y I. M. Navon. "A Dual-Weighted Approach to Order Reduction in 4DVAR Data Assimilation". Monthly Weather Review 136, n.º 3 (1 de marzo de 2008): 1026–41. http://dx.doi.org/10.1175/2007mwr2102.1.
Texto completoJiang, Jing-Wei, Yang Yang, Tong-Wei Ren, Fei Wang y Wei-Xi Huang. "Evolutionary Optimisation for Reduction of the Low-Frequency Discrete-Spectrum Force of Marine Propeller Based on a Data-Driven Surrogate Model". Journal of Marine Science and Engineering 9, n.º 1 (25 de diciembre de 2020): 18. http://dx.doi.org/10.3390/jmse9010018.
Texto completoPrével, Arthur, Vinca Rivière, Jean-Claude Darcheville, Gonzalo P. Urcelay y Ralph R. Miller. "Excitatory second-order conditioning using a backward first-order conditioned stimulus: A challenge for prediction error reduction". Quarterly Journal of Experimental Psychology 72, n.º 6 (21 de agosto de 2018): 1453–65. http://dx.doi.org/10.1177/1747021818793376.
Texto completoRaia, Maria Raluca, Mircea Ruba, Raul Octavian Nemes y Claudia Martis. "Artificial Neural Network and Data Dimensionality Reduction Based on Machine Learning Methods for PMSM Model Order Reduction". IEEE Access 9 (2021): 102345–54. http://dx.doi.org/10.1109/access.2021.3095668.
Texto completoSzalai, Robert. "Invariant spectral foliations with applications to model order reduction and synthesis". Nonlinear Dynamics 101, n.º 4 (31 de agosto de 2020): 2645–69. http://dx.doi.org/10.1007/s11071-020-05891-1.
Texto completoWen, Bin, Zheng Li y Nicholas Zabaras. "Thermal Response Variability of Random Polycrystalline Microstructures". Communications in Computational Physics 10, n.º 3 (septiembre de 2011): 607–34. http://dx.doi.org/10.4208/cicp.200510.061210a.
Texto completoGosea, Ion Victor. "Exact and Inexact Lifting Transformations of Nonlinear Dynamical Systems: Transfer Functions, Equivalence, and Complexity Reduction". Applied Sciences 12, n.º 5 (23 de febrero de 2022): 2333. http://dx.doi.org/10.3390/app12052333.
Texto completoAbbasi, Mohammad Hossein, Laura Iapichino, Wil Schilders y Nathan van de Wouw. "A data-based stability-preserving model order reduction method for hyperbolic partial differential equations". Nonlinear Dynamics 107, n.º 4 (10 de enero de 2022): 3729–48. http://dx.doi.org/10.1007/s11071-021-07094-8.
Texto completoNeggers, Jan, Olivier Allix, François Hild y Stéphane Roux. "Big Data in Experimental Mechanics and Model Order Reduction: Today’s Challenges and Tomorrow’s Opportunities". Archives of Computational Methods in Engineering 25, n.º 1 (28 de julio de 2017): 143–64. http://dx.doi.org/10.1007/s11831-017-9234-3.
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