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Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1699
DC FieldValueLanguage
dc.contributor.authorNguyen Ngoc Thuy Linhen_US
dc.date.accessioned2023-10-01T08:57:45Z-
dc.date.available2023-10-01T08:57:45Z-
dc.date.issued2023-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1699-
dc.description.abstractThis study employs a predictive model to demonstrate the impacts of geological conditions, operating conditions and structural parameters on the total load. The model’s accuracy is confirmed by validating with the force from the tunneling processen_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectOnline process dataen_US
dc.subjectMachine learningen_US
dc.subjectMechanized tunnelingen_US
dc.titleOnline process data utilization using machine learning techniques in mechanized tunnelingen_US
dc.typeThesisen_US
item.fulltextWith Fulltext-
item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Computational Engineering (CompEng)
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