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A machine learning based methodology for anomaly detection in dam behaviour.

Type of activity
Theses
Other related units
Department of Civil and Environmental Engineering
Defense's date
2017-02-23
URL
http://hdl.handle.net/2117/107943 Open in new window
Abstract
Dam behaviour is difficult to predict with high accuracy. Numerical models for structural calculation solve the equations of continuum mechanics, but are subject to considerable uncertainty as to the characterisation of materials, especially with regard to the foundation. As a result, these models are often incapable to calculate dam behaviour with sufficient precision. Thus, it is difficult to determine whether a given deviation between model results and monitoring data represent a relevant ano...
Group of research
(MC)2 - UPC Computational continuum mechanics
GMNE - Numerical Methods in Engineering Group
Citation
Salazar González, F. "A machine learning based methodology for anomaly detection in dam behaviour". Tesi doctoral, UPC, Departament d'Enginyeria Civil i Ambiental, 2017.

Participants

  • Salazar González, Fernando  (author)
  • Oñate Ibáñez de Navarra, Eugenio  (director)
  • Escuder Bueno, Ignacio  (secretary)
  • Polimon Lopez, Jose  (president)
  • Tomé Caires da mata, Juan  (chair)
  • Toledo Municio, Miguel Angel  (director)

Attachments