Review of methods for automation of quality control on hydrologic time series and considerations for - detaljert visning

Review of methods for automation of quality control on hydrologic time series and considerations for a research approach at NVE

Trond Reitan
Bok Engelsk 2022


Utgitt	Oslo : NVE , 2022
Omfang	46 s. : ill. (noen kol.)
Opplysninger	Har bibliografi. - Sammendrag: This report contains a literature study on the topic of automatic anomaly detection in time series using machine learning. The study has been carried out in order to see what the state of field is, both in academic circles and in real world applications in institutions that gather hydrologic or meteorologic time series. The academic research is far more advanced of what hydrologic and meteorologic institutions are currently implementing, however some initial forays into applying the theory by such institutions have started. The research is however applied to time series across a much wider spectrum of applications, so it is hard to judge how well a method works for NVE purposes. Therefore, testing at NVE is required to evaluate how well various methods work. Performance should be based on how good the end results are as well as their speed and robustness
Emner	Analyser Anomaly detection Hydrologi Hydrological time series Vis mer... Machine learning Tidsserier
Geografisk emneord	Norge
Dewey	556(05)
ISBN	978-82-410-2206-7
ISSN	1501-2832