MARS Applications in Geotechnical Engineering Systems
Multi-Dimension with Big Data
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Beschreibung
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.
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.
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 efficiency Provides numerous examples and highlights geotechnical applications of big data to facilitate reader comprehension
Autor*in
Wengang Zhang
Themen in »MARS Applications in Geotechnical Engineering Systems«
Multivariate Adaptive Regression Splines Geotechnical Engineering System Big Data Surrogate Model Meta Model Performance Functions Pile Drivability Limit State Funtions