MARS Applications in Geotechnical Engineering Systems Multi-Dimension with Big Data
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 mathematicall...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2020, 2020
|
| Edition: | 1st ed. 2020 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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. |
|---|---|
| Physical Description: | XXI, 240 p. 99 illus., 64 illus. in color online resource |
| ISBN: | 9789811374227 |