An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method

Efficient Bayesian Multivariate Surface Regression

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, Artistic and Efficient Modification of the Inversion Method

     The simplest and fastest way of producing an acceptable and accurate cast is by adopting the two-pour or inversion method. This process is slightly cumbersome and messy due to difficulty of access. A much more efficient, easy and artistic way of accomplishing it is described by adopting a Rotating Cake Icing Table with a Silicone Baking Mat on top as an autoclavable non-stick barrier.    

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...

Determining Effective Factors on Forest Fire Using the Compound of Multivariate Adaptive Regression Spline and Genetic Algorithm, a Case Study: Golestan, Iran

Determining Effective Factors on Forest Fire Using the Compound of Multivariate Adaptive Regression Spline and Genetic Algorithm, a Case Study: Golestan, Iran    Pahlavani, P., Assistant professor at School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran Raei, A., PhD Candidate of GIS at School of Surveying and Geospatial Engineering, College of Engineeri...