Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Condition: New.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New.
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 264 pages. 9.25x6.10x0.79 inches. In Stock.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore Mai 2019, 2019
ISBN 10: 981137421X ISBN 13: 9789811374210
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 981137421X ISBN 13: 9789811374210
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Seller: liu xing, Nanjing, JS, China
paperback. Condition: New. Paperback. Pub Date: 2019-01-01 Pages: 240 Language: English Publisher: Science Press Many geotechnical problems rely on empirical methods to design equations or expressions chart to determine the response of the system to input variables. MARS Applications in Geotechnical En .
Seller: Mispah books, Redhill, SURRE, United Kingdom
Hardcover. Condition: New. New. book.
Language: English
Published by Springer Nature Singapore Mai 2019, 2019
ISBN 10: 981137421X ISBN 13: 9789811374210
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 264 pp. Englisch.
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) and its applications Introduces simple algorithms that are easy to interpret and deliver good computational efficien.
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. MARS Applications in Geotechnical Engineering Systems | Multi-Dimension with Big Data | Wengang Zhang | Buch | xxi | Englisch | 2019 | Springer Singapore | EAN 9789811374210 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.