Name
Abstract | ||
|---|---|---|
We developed a levee health monitoring system within the UrbanFlood project funded under the EU 7th Framework Programme. A novel real-time levee health assessment Artificial Intelligence system is developed using data-driven methods. The system is implemented in the UrbanFlood early warning system. We present the application of dedicated signal processing methods for detection of leakage through the water retaining dam and subsequent analysis of the measurements collected from one of the UrbanFlood pilot levees at the Rhine river in Germany. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.procs.2013.05.407 | 2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE |
Keywords | Field | DocType |
signal analysis, levee health monitoring, UrbanFlood project, leakage detection, one-side classification | Data mining,Signal processing,Monitoring system,Levee,Computer science,Real-time computing,Health assessment,Early warning system,Artificial Intelligence System | Conference |
Volume | ISSN | Citations |
18 | 1877-0509 | 4 |
PageRank | References | Authors |
0.62 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander L. Pyayt | 1 | 5 | 1.35 |
| Alexey P. Kozionov | 2 | 5 | 1.01 |
| Ilya I. Mokhov | 3 | 5 | 1.01 |
| Bernhard Lang | 4 | 5 | 1.01 |
| Valeria V. Krzhizhanovskaya | 5 | 194 | 30.20 |
| Peter M. A. Sloot | 6 | 3095 | 513.51 |