Publications in collaboration with researchers from Universidad de Sevilla (11)

2023

  1. Boundary element analysis of three-dimensional thermomechanical orthotropic frictional contact problems

    AIP Conference Proceedings

2022

  1. 3D thermoelastic solids under non-linear interface thermal and orthotropic frictional contact conditions

    International Journal for Numerical Methods in Engineering, Vol. 123, Núm. 11, pp. 2631-2659

2020

  1. A boundary element procedure to analyze the thermomechanical contact problem in 3D microelectronic packaging

    Engineering Analysis with Boundary Elements, Vol. 115, pp. 28-39

  2. Non-linear interface thermal conditions in three-dimensional thermoelastic contact problems

    Computers and Structures, Vol. 241

  3. Thermoelastic influence of convective and conduction interstitial conditions on the size of the contact zone in three-dimensional receding thermoelastic contact problem

    Acta Mechanica, Vol. 231, Núm. 7, pp. 3065-3084

2019

  1. The effect of conduction and convective conditions at interstitial regions on 3D thermoelastic contact problems

    Engineering Analysis with Boundary Elements, Vol. 107, pp. 243-256

2017

  1. Impact of plot size and model selection on forest biomass estimation using airborne LiDAR: A case study of pine plantations in southern Spain

    Journal of Forest Science, Vol. 63, Núm. 2, pp. 88-97

2016

  1. A preliminary study of the suitability of deep learning to improve LiDAR-derived biomass estimation

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest

    European Journal of Remote Sensing, Vol. 49, pp. 185-204

2014

  1. Evolutionary feature selection to estimate forest stand variables using LiDAR

    International Journal of Applied Earth Observation and Geoinformation, Vol. 26, Núm. 1, pp. 119-131

2011

  1. A comparative study between two regression methods on LiDAR data: A case study

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)