Flood forecasting in large rivers with data-driven models

Results from the application of adaptive neuro-fuzzy inference system (ANFIS) to forecast water levels at 3 stations along the mainstream of the Lower Mekong River are reported in this paper. The study investigated the effects of including water levels from upstream stations and tributaries, and rai...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Natural hazards (Dordrecht) 2014-03, Vol.71 (1), p.767-784
Hauptverfasser:	Nguyen, Phuoc Khac-Tien, Chua, Lloyd Hock-Chye, Son, Lam Hung
Format:	Artikel
Sprache:	eng
Schlagworte:	Civil Engineering Earth and Environmental Science Earth Sciences Earth, ocean, space Engineering and environment geology. Geothermics Environmental Management Environmental policy Errors Exact sciences and technology Flood control Flood forecasting Floods Forecasting Freshwater Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Hazards Hydrogeology Inclusions Indexes Inference Mathematical models Mekong river Natural Hazards Natural hazards: prediction, damages, etc Original Paper Rainfall Rivers Stations Tributaries Upstream Water Water levels Weather forecasting
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!