Assessment of machine learning methods as a tool in detecting leakages
Kristian Gundersen
University of Bergen
Kristian Gundersen has a master in applied and computational mathematics from UiB from 2010. He started to work as a PhD on the BayMoDe project in January 2017. The aim of the project is to develop new methods for detection of CO2- leakages using a Bayesian approach and machine learning techniques. Kristian has also five years experience as a Safety engineer at Safetec Nordic.
Authors
- Kristian Gundersen (University of Bergen)
- Guttorm Alendal (University of Bergen)
- Hans Skaug (University of Bergen)
- Helge Avlesen (University of Bergen)
- Jerry Blackford (Plymouth Marine Laboratory)
- Baixin Chen (Heriot-Watt University)
- Marius Dewar (Heriot-Watt University)
- Jarle Berntsen (UIB)
Topic Areas
Other , EU project SUCCESS
Session
Poster » Poster session (15:20 - Tuesday, 13th June)
