Übersicht			Auf mobile öffnen

Lieferstatus:	i.d.R. innert 14-24 Tagen versandfertig
Veröffentlichung:	Mai 2019
Genre:	Naturwissensch., Medizin, Technik
	B / Big Data / Big Data/Analytics / Business mathematics & systems / Computer networking & communications / Databases / Distributed databases / Earth Sciences / engineering / Engineering geology / Engineering—Geology / Foundations / Geochemistry / Geoengineering / Geoengineering, Foundations, Hydraulics / Geotechnical engineering / Geotechnical Engineering & Applied Earth Sciences / Geotechnical Engineering and Applied Earth Sciences / Hydraulics / Input-output equipment (Computers) / Input/Output and Data Communications / IT in Business
ISBN:	9789811374210
EAN-Code:	9789811374210
Verlag:	Springer Nature Singapore
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 241 mm / B 160 mm / D 20 mm
Gewicht:	565 gr
Seiten:	264
Zus. Info:	HC runder Rücken kaschiert
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book presents the application of a comparatively simple nonparametric regression algorithm, known as the multivariate adaptive regression splines (MARS) surrogate model, which can be used to approximate the relationship between the inputs and outputs, and express that relationship mathematically. The book first describes the MARS algorithm, then highlights a number of geotechnical applications with multivariate big data sets to explore the approach's generalization capabilities and accuracy. As such, it offers a valuable resource for all geotechnical researchers, engineers, and general readers interested in big data analysis.