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@ARTICLE{Rudack:993396,
author = {Rudack, Maximilian Markus and Rom, Christian Michael and
Bruckmeier, Lukas and Moser, Mario Niclas and Pustal, Björn
and Bührig-Polaczek, Andreas},
title = {{R}ecurrent neural networks as virtual cavity pressure and
temperature sensors in high-pressure die casting},
journal = {The international journal of advanced manufacturing
technology},
volume = {134},
number = {7/8},
issn = {0268-3768},
address = {London},
publisher = {Springer},
reportid = {RWTH-2024-08704},
pages = {3267-3280},
year = {2024},
cin = {526110 / 520000 / 080067 / 111410 / 110000 / 417510 /
417200},
ddc = {670},
cid = {$I:(DE-82)526110_20140620$ / $I:(DE-82)520000_20140620$ /
$I:(DE-82)080067_20181221$ / $I:(DE-82)111410_20170801$ /
$I:(DE-82)110000_20140620$ / $I:(DE-82)417510_20140620$ /
$I:(DE-82)417200_20140620$},
pnm = {WS-A.I - Physical Infrastructure Supporting Digital Shadows
(X080067-WS-A.I) / WS-B2.II - Discontinuous Production
(X080067-WS-B2.II) / WS-B1.II - Integrated Structural Health
Engineering (X080067-WS-B1.II) / DFG project
G:(GEPRIS)390621612 - EXC 2023: Internet of Production (IoP)
(390621612) / OAPKF - Open-Access-Publikation mit
Unterstützung der RWTH Aachen University (021000-OAPKF)},
pid = {G:(DE-82)X080067-WS-A.I / G:(DE-82)X080067-WS-B2.II /
G:(DE-82)X080067-WS-B1.II / G:(GEPRIS)390621612 /
G:(DE-82)021000-OAPKF},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001302282000001},
doi = {10.1007/s00170-024-14270-8},
url = {https://publications.rwth-aachen.de/record/993396},
}
Gast ::