Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	August 2016
Genre:	Naturwissensch., Medizin, Technik
	B / Earth and Environmental Science / Earth Sciences / Engineering geology / Engineering—Geology / Foundations / Geochemistry / Geoengineering / Geoengineering, Foundations, Hydraulics / Hydraulics / Hydrogeology / Hydrology / Hydrology & the hydrosphere / Hydrology/Water Resources / Meteorology & climatology / Water
ISBN:	9783319350288
EAN-Code:	9783319350288
Verlag:	Springer Nature EN
Einband:	Kartoniert
Sprache:	English
Serie:	#01 - Earth Systems Data and Models
Dimensionen:	H 235 mm / B 155 mm / D 14 mm
Gewicht:	4102 gr
Seiten:	250
Illustration:	XV, 250 p. 172 illus., 59 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Zus. Info:	Previously published in hardcover
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.