Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks

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SYSNO	0541776
Title	Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks
Author(s)	Dropka, N. (DE) Ecklebe, S. (DE) Holeňa, Martin (UIVT-O)_{SAI, RID}
Corespondence/senior	Dropka, N. - Korespondující autor
Source Title	Crystals. Roč. 11, č. 2 (2021). - : MDPI
Article number	138
Document Type	Článek v odborném periodiku
Grant	GA18-18080S GA ČR - Czech Science Foundation (CSF), CZ - Czech Republic
Institutional support	UIVT-O - RVO:67985807
Language	eng
Country	CH
Keywords	neural networks * crystal growth * GaAs * process control * digital twins
URL	http://hdl.handle.net/11104/0319303
Permanent Link	http://hdl.handle.net/11104/0319303

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Number of the records: 1