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Auflistung nach Schlagwort "Deep learning"
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Guo, Hongwei; Zhuang, Xiaoying; Fu, Xiaolong; Zhu, Yunzheng; Rabczuk, Timon
(Berlin ; Heidelberg : Springer, 2023)
We present a physics-informed deep learning model for the transient heat transfer analysis of three-dimensional functionally graded materials (FGMs) employing a Runge–Kutta discrete time scheme. Firstly, the governing ...
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Baldan, Marco; Baldan, Giacomo; Nacke, Bernard
(Stevenage [u.a] : IET, 2021)
Electromagnetics (EM) can be described, together with the constitutive laws, by four PDEs, called Maxwell's equations. “Quasi-static” approximations emerge from neglecting particular couplings of electric and magnetic field ...
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Guo, Hongwei; Zhuang, Xiaoying; Chen, Pengwan; Alajlan, Naif; Rabczuk, Timon
(London : Springer, 2022)
We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key ...
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Koetsier, C.; Busch, S.; Sester, M.
(Göttingen : Copernicus GmbH, 2019)
The environment of the vehicle can significantly influence the driving situation. Which conditions lead to unsafe driving behaviour is not always clear, also not to a human driver, as the causes might be unconscious, and ...
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Xuan, Quy Le; Adhisantoso, Yeremia G.; Munderloh, Marco; Ostermann, Jörn
(Amsterdam [u.a.] : Elsevier, 2023)
Reliably predicting Remaining Useful Life (RUL) is crucial for reducing asset maintenance costs. Deep learning emerges as a powerful data-driven method capable of predicting RUL based on historical operating data. However, ...
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Müller-Budack, Eric
(Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2022)
Das World Wide Web und die sozialen Medien übernehmen im heutigen Informationszeitalter eine wichtige Rolle für die Vermittlung von Nachrichten und Informationen. In der Regel werden verschiedene Modalitäten im Sinne der ...