%0 Thesis %1 phd/basesearch/Nybo09 %A Nybø, Roar %D 2009 %K %T Efficient Drilling Problem Detection: Early fault detection by the combination of physical models and artificial intelligence.

@phdthesis{phd/basesearch/Nybo09, added-at = {2023-12-14T16:07:05.000+0100}, author = {Nybø, Roar}, biburl = {https://www.bibsonomy.org/bibtex/2422a8d68590c965eac404a9d604b6419/admin}, ee = {https://www.base-search.net/Record/65d16cae82f352dbb3e63a8d3f3983f7dbe2ac00c8905f25ceabbb63311e17cf}, interhash = {f3c2acabd4352420692e36c4e3f1bc37}, intrahash = {422a8d68590c965eac404a9d604b6419}, keywords = {}, note = {base-search.net (ftntnutrondircom:oai:brage.bibsys.no:11250/239305)}, school = {Norwegian University of Science and Technology, Trondheim, Norway}, timestamp = {2023-12-14T16:07:05.000+0100}, title = {Efficient Drilling Problem Detection: Early fault detection by the combination of physical models and artificial intelligence.}, year = 2009 }