Open AccessPrediction of synthetic oil parameters by artificial neural networks at durability tests of porous bearings
Author(s) -
Artur Król,
Krzysztof Gocman
Publication year - 2016
Publication title -
proceedings of the estonian academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.266
H-Index - 20
eISSN - 1736-7530
pISSN - 1736-6046
DOI - 10.3176/proc.2016.2.08
Subject(s) - durability , artificial neural network , porosity , engineering , artificial intelligence , computer science , materials science , petroleum engineering , geotechnical engineering , composite material
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