References
- https://en.wikipedia.org/wiki/Model_order_reduction
- Zambrano, V.; Brase, M.; Hernández-Gascón, B.; Wangenheim, M.; Gracia, L.A.; Viejo, I.; Izquierdo, S.; Valdés, J.R. “A Digital Twin for Friction Prediction in Dynamic Rubber Applications with Surface Textures”, Lubricants 9 (5), 57, 2021. DOI: 10.3390/lubricants9050057
- Hornik, K., Stinchcombe, M., White, H. “Multilayer Feedforward Networks are Universal Approximators”, Neural Networks 2 (5), pp. 359 – 366, 1989.
- Graves, A. “Supervised Sequence Labelling with Recurrent Neural Networks”, Springer Berlin, Heidelberg, 13 April 2014. eISSN 978-3-642-24797-2
- https://en.wikipedia.org/wiki/Proper_orthogonal_decomposition
- Danko, J., NEMEC, T., MILESICH, T., MAGDOLEN, Ľ.: “Dynamic Stiffness Determination of the Rubber Bushing Fem Modelwith Viscoelastic Material Behaviour” Strojnícky časopis – Journal of Mechanical Engineering 72 (3), pp. 113 – 120, 2022, DOI: 10.2478/scjme-2022-0045
- Bernáth, M., Danko, J., Magdolen, Ľ., Milesich, T., Nemec, T.: “Analysis and Design of Rear Twin Electric Powertrain Mounting System in E-Up Boost“, Strojnícky časopis – Journal of Mechanical Engineering 73 (2), pp. 9 – 14, 2023. DOI: 10.2478/sc-jme-2023-0018
- Bucha, J., Danko, J., Milesich, T., Nemec, T., Magdolen, Ľ. “Comparison of FEM Simulations of Rubber-Metal Mount Element” Strojnícky časopis – Journal of Mechanical Engineering 72 (1), pp. 15 – 22, 2022. DOI: 10.2478/scjme-2022-0002