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MARS applications in geotechnical engineering systems = multi-dimension with big data /

Record Type:	Electronic resources : Monograph/item
Title/Author:	MARS applications in geotechnical engineering systems/ by Wengang Zhang.
Reminder of title:	multi-dimension with big data /
Author:	Zhang, Wengang.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xxi, 240 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- MARS methodology -- Simple MARS modeling examples -- MARS use in prediction of collapse potential for compacted soils -- MARS use in prediction of diaphragm wall deflections in soft clays -- MARS use in HP-pile drivability assessment -- MARS use in assessment of soil liquefaction -- MARS use in evaluating entry-type excavation stability -- Summary and conclusions.
Contained By:	Springer eBooks
Subject:	Input/Output and Data Communications. -
Online resource:	https://doi.org/10.1007/978-981-13-7422-7
ISBN:	9789811374227

MARS applications in geotechnical engineering systems = multi-dimension with big data /
Zhang, Wengang.

MARS applications in geotechnical engineering systemsmulti-dimension with big data /[electronic resource] :by Wengang Zhang. - Singapore :Springer Singapore :2020. - xxi, 240 p. :ill., digital ;24 cm.

Introduction -- MARS methodology -- Simple MARS modeling examples -- MARS use in prediction of collapse potential for compacted soils -- MARS use in prediction of diaphragm wall deflections in soft clays -- MARS use in HP-pile drivability assessment -- MARS use in assessment of soil liquefaction -- MARS use in evaluating entry-type excavation stability -- Summary and conclusions.

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.

ISBN: 9789811374227

Standard No.: 10.1007/978-981-13-7422-7doiSubjects--Topical Terms:

893593
Input/Output and Data Communications.

LC Class. No.: QA278

Dewey Class. No.: 519.535

MARS applications in geotechnical engineering systems = multi-dimension with big data /
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100 1 $a Zhang, Wengang. $3 3442641
245 1 0 $a MARS applications in geotechnical engineering systems $h [electronic resource] : $b multi-dimension with big data / $c by Wengang Zhang.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xxi, 240 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- MARS methodology -- Simple MARS modeling examples -- MARS use in prediction of collapse potential for compacted soils -- MARS use in prediction of diaphragm wall deflections in soft clays -- MARS use in HP-pile drivability assessment -- MARS use in assessment of soil liquefaction -- MARS use in evaluating entry-type excavation stability -- Summary and conclusions.
520 $a 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.
650 2 4 $a Input/Output and Data Communications. $3 893593
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650 0 $a Geotechnical engineering. $3 2058689
650 0 $a Big data. $3 2045508
650 1 4 $a Geoengineering, Foundations, Hydraulics. $3 1001783
650 2 4 $a Geotechnical Engineering & Applied Earth Sciences. $3 1565915
650 2 4 $a Big Data. $3 3134868
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856 4 0 $u https://doi.org/10.1007/978-981-13-7422-7
950 $a Engineering (Springer-11647)