Description
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.
Table of 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.
