Paulino José García Nieto

TL;DR: In this paper, a support vector machine (SVM) was used to estimate the state of charge (SOC) of a high capacity LiFeMnPO4 battery cell from an experimental dataset using a SVM approach.

TL;DR: In this article, a multivariate adaptive regression splines (MARS) technique was used to estimate the state of charge (SOC) of a high capacity LiFePO4 battery cell from an experimental dataset obtained in the University of Oviedo Battery Laboratory.

TL;DR: In this article, the main hygrothermal properties of different mixes of lightweight concrete (LWC) produced from expanded clay are investigated, and the results and conclusions reached in this work are exposed.

TL;DR: The present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines that combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs).

TL;DR: A new method for defining rock stability areas of the critical span graph is presented, which applies machine learning classifiers (support vector machine and extreme learning machine) and the results show a reasonable correlation with previous guidelines.