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MARS Applications in Geotechnical Engineering Systems [electronic resource] : Multi-Dimension with Big Data / by Wengang Zhang.

By: Zhang, Wengang [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: XXI, 240 p. 99 illus., 64 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811374227.Subject(s): Engineering geology | Geotechnical engineering | Big data | Quantitative research | Computer input-output equipment | Geoengineering | Geotechnical Engineering and Applied Earth Sciences | Big Data | Data Analysis and Big Data | Input/Output and Data CommunicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 624.15 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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. .
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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. .

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