Publicaciones en colaboración con investigadores/as de Universidad de Salamanca (20)

2023

  1. PSO-PARSIMONY: A method for finding parsimonious and accurate machine learning models with particle swarm optimization. Application for predicting force–displacement curves in T-stub steel connections

    Neurocomputing, Vol. 548

  2. Preface

    Lecture Notes in Networks and Systems

  3. Preface

    Lecture Notes in Networks and Systems

  4. Preface

    Lecture Notes in Networks and Systems

  5. Preface

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

  6. Preface

    Lecture Notes in Networks and Systems

  7. Work-in-Progress: Building Up Employability Skills and Social Responsibility in the University of La Rioja Industrial Engineering Degrees

    Lecture Notes in Networks and Systems

2022

  1. Efectos de la pandemia en metodologías de aprendizaje activo. Medidas de fortalecimiento

    La innovación como motor para la transformación de la enseñanza universitaria (Universidad de La Rioja), pp. 51-62

  2. Fortaleciendo el aprendizaje activo en tiempos de pandemia

    Jornada de Innovación docente de la Universidad de La Rioja 2021: #InnovaDocenteUR: libro de resúmenes

  3. Preface

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

2021

  1. Active learning methodologies in STEM degrees jeopardized by COVID19

    IEEE Global Engineering Education Conference, EDUCON

  2. Editorial: Special issue HAIS17-IGPL

    Logic Journal of the IGPL

  3. PSO-PARSIMONY: A New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections

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

  4. PSO-PARSIMONY: a New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections

    Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings

2017

  1. Preface

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