Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach

Data Driven Adaptive Spline Smoothing

In classical smoothing splines, the smoothness is controlled by a single smoothing parameter that penalizes the roughness uniformly across the whole domain. Adaptive smoothing splines extend this framework to allow the smoothing parameter to change in the domain, adapting to the change of roughness. In this article we propose a data driven method to nonparametrically model the penalty function....

Relevance vector machine and multivariate adaptive regression spline for modelling ultimate capacity of pile foundation

This study examines the capability of the Relevance Vector Machine (RVM) and Multivariate Adaptive Regression Spline (MARS) for prediction of ultimate capacity of driven piles and drilled shafts. RVM is a sparse method for training generalized linear models, while MARS technique is basically an adaptive piece-wise regression approach. In this paper, pile capacity prediction models are developed...

ESTIMATING DRYING SHRINKAGE OF CONCRETE USING A MULTIVARIATE ADAPTIVE REGRESSION SPLINES APPROACH

In the present study, the multivariate adaptive regression splines (MARS) technique is employed to estimate the drying shrinkage of concrete. To this purpose, a very big database (RILEM Data Bank) from different experimental studies is used. Several effective parameters such as the age of onset of shrinkage measurement, age at start of drying, the ratio of the volume of the sample on its drying...

A Simple Roughness Penalty Approach to Regression Spline Estimation

A regression spline is a piecewise polynomial function whose highest order nonzero derivative takes jumps at xed \knots." Usually regression splines are smoothed by deleting nonessential knots, or equivalently setting the jumps at those knots to zero. A method that is simpler to implement and has lower computational cost is to shrink the jumps at all knots towards zero by using a penalty functi...

Multivariate Adaptive Regression Splines