- Data-driven modelling for flood defence structure analysis
- 2nd European Conference on FLOODrisk Management
- Book/source title
- Comprehensive flood risk management: research for policy and practice
- Pages (from-to)
- CRC Press
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
We present a data-driven modelling approach for detection of anomalies in flood defences (levees, dykes, dams, embankments) equipped with sensors. An auto-regressive linear model and feed-forward neural network were applied for modelling a transfer function between the sensors. This approach has been validated on a dike in Boston, UK—one of the pilot sites of the
UrbanFlood project— that showed both normal and abnormal sensor behaviour. Comparison of the linear and non-linear mod- els is presented. The suggested model-based anomaly detection approach will extend functionality of the developed Artificial Intelligence component of the UrbanFlood Early Warning System.
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library, or send a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.