Publications dans lesquelles il/elle collabore avec Francisco Martínez Álvarez (36)

2021

  1. A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets

    Advances in Intelligent Systems and Computing

  2. A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets

    15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020

  3. On the Performance of Deep Learning Models for Time Series Classification in Streaming

    15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020

  4. On the Performance of Deep Learning Models for Time Series Classification in Streaming

    Advances in Intelligent Systems and Computing

2020

  1. Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model

    Big data, Vol. 8, Núm. 4, pp. 308-322

2019

  1. A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system

    IEEE Access, Vol. 7, pp. 120840-120856

  2. Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses

    Advances in Intelligent Systems and Computing

2018

  1. A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information

    Environmental Modelling and Software, pp. 52-61

  2. Big data analytics for discovering electricity consumption patterns in smart cities

    Energies, Vol. 11, Núm. 3

  3. Data science and big data in energy forecasting

    Energies, Vol. 11, Núm. 11

  4. SmartFD: A real big data application for electrical fraud detection

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

2017

  1. Applications of Computational Intelligence in Time Series

    Computational Intelligence and Neuroscience

  2. Recent advances in energy time series forecasting

    Energies

2016

  1. Improving a multi-objective evolutionary algorithm to discover quantitative association rules

    Knowledge and Information Systems, Vol. 49, Núm. 2, pp. 481-509

  2. Obtaining optimal quality measures for quantitative association rules

    Neurocomputing, Vol. 176, pp. 36-47

2015

  1. A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

    Neurocomputing, Vol. 167, pp. 24-31

  2. A survey on data mining techniques applied to electricity-related time series forecasting

    Energies, Vol. 8, Núm. 11, pp. 13162-13193

2014

  1. A comparative study of machine learning regression methods on LiDAR data: A case study

    Advances in Intelligent Systems and Computing

  2. Selecting the best measures to discover quantitative association rules

    Neurocomputing, Vol. 126, pp. 3-14

  3. TriGen: A genetic algorithm to mine triclusters in temporal gene expression data

    Neurocomputing, Vol. 132, pp. 42-53