The support vector classifier (SVC) is one of the most powerful machine learning algorithms.
This algorithm has been accepted as an effective method in three-dimensional geological …

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest
class and structure variables collected in forest inventories as functions of satellite-based …

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in
soils. To that extent, the sorption and retention of these metals were studied and the soil …

This article introduces a probabilistic machine learning framework for the uncertainty
quantification (UQ) of electronic circuits based on the Gaussian process regression (GPR) …

This article proposes a methodology for the analysis of the causes and types of workplace
accidents (in this paper we focus specifically on floor-level falls). The approach is based on …

Grade estimation is a critical issue in mineral resource evaluation, being extensively
investigated by data mining techniques. In this paper, a hybrid method composed of back …

Support vector machine (SVM) classification models were constructed using a radial basis
functions (RBF). These models were used for classification according to dissolved oxygen …

Accurate prediction of thermophysical properties of compressed air is specifically crucial in
optimal design and analyzing performance of a Compressed Air Energy Storage (CAES) …

In this paper, the authors apply different classification techniques in order to provide 24 h
advance forecasts of the daily peaks of SO 2 and PM10 concentrations in the Bay of …

In this work, we create a quality map of a slate deposit, using the results of an investigation
based on surface geology and continuous core borehole sampling. Once the quality of the …