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pro vyhledávání: '"Wilhelm Söderkvist Vermelin"'
Autor:
Wilhelm Söderkvist Vermelin, Madhav Mishra, Mattias P. Eng, Dag Andersson, Konstantinos Kyprianidis
Publikováno v:
International Journal of Prognostics and Health Management, Vol 15, Iss 2 (2024)
Remaining useful life prediction models are a central aspect of developing modern and capable prognostics and health management systems. Recently, such models are increasingly data-driven and based on various machine learning techniques, in particula
Externí odkaz:
https://doaj.org/article/099a6ab4995c44699c1b429dea8c3bcf
Publikováno v:
Annual Conference of the PHM Society. 14
Canonical deep learning-based Remaining Useful Life (RUL) prediction relies on supervised learning methods which in turn requires large data sets of run-to-failure data to ensure model performance. In a large class of cases, run-to-failure data is di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d8e785bc8f078fcf8821426607661a9
https://doi.org/10.36001/phmconf.2022.v14i1.3222
https://doi.org/10.36001/phmconf.2022.v14i1.3222
Autor:
Wilhelm, Söderkvist Vermelin
Experimental data suggest that the universe is homogeneous and isotropic on sufficiently large scales. An exact solution of the Einstein field equations exists for a homogeneous and isotropic universe, also known as a Friedmann-Lemaître-Robertson-Wa
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43257
