Quality monitoring in vibro ground improvement: A hybrid machine learning approach
Publikationen: Beitrag in Fachzeitschrift › Artikel › Forschung › (peer-reviewed)
Standard
in: Geomechanics and tunnelling, Jahrgang 15.2022, Nr. 5, 04.10.2022, S. 658-664.
Publikationen: Beitrag in Fachzeitschrift › Artikel › Forschung › (peer-reviewed)
Harvard
APA
Vancouver
Author
Bibtex - Download
}
RIS (suitable for import to EndNote) - Download
TY - JOUR
T1 - Quality monitoring in vibro ground improvement
T2 - A hybrid machine learning approach
AU - Terbuch, Anika
AU - Zöhrer, Alexander
AU - Winter, Vincent
AU - O'Leary, Paul
AU - Khalilimotlaghkasmaei, Negin
AU - Steiner, Gernot
N1 - Publisher Copyright: © 2022, Ernst und Sohn. All rights reserved.
PY - 2022/10/4
Y1 - 2022/10/4
KW - Artificial Ingelligence in Geotechnical Engineering
KW - General
KW - hybrid learning
KW - KPI analysis
KW - outlier detection
KW - quality monitoring
KW - time-series
KW - vibro ground improvement
UR - http://www.scopus.com/inward/record.url?scp=85139267708&partnerID=8YFLogxK
U2 - 10.1002/geot.202200028
DO - 10.1002/geot.202200028
M3 - Article
AN - SCOPUS:85139267708
VL - 15.2022
SP - 658
EP - 664
JO - Geomechanics and tunnelling
JF - Geomechanics and tunnelling
SN - 1865-7362
IS - 5
ER -