Publications by the researcher in collaboration with ANTONIO BERNARDO SANCHEZ (21)

2025

  1. Interpretable Machine Learning Models for Estimating Electric Energy Consumption in Steel Industries

    Mathematics, Vol. 13, Núm. 21

  2. Inverse Gravimetric Problem Solving via Prolate Ellipsoidal Parameterization and Particle Swarm Optimization

    Mathematics, Vol. 13, Núm. 12

2024

  1. Predicting the critical superconducting temperature using the random forest, MLP neural network, M5 model tree and multivariate linear regression

    Alexandria Engineering Journal, Vol. 86, pp. 144-156

2023

  1. Method for the Detection of Functional Outliers Applied to Quality Monitoring Samples in the Vicinity of El Musel Seaport in the Metropolitan Area of Gijón (Northern Spain)

    Mathematics, Vol. 11, Núm. 12

2021

  1. A new hybrid model to foretell thermal power efficiency from energy performance certificates at residential dwellings applying a Gaussian process regression

    Neural Computing and Applications, Vol. 33, Núm. 12, pp. 6627-6640

  2. Modelling energy performance using a new hybrid DE/MARS–based approach for fossil-fuel thermal power stations

    Environmental Science and Pollution Research, Vol. 28, Núm. 4, pp. 4417-4429

2020

  1. A hybrid predictive approach for chromium layer thickness in the hard chromium plating process based on the differential evolution/gradient boosted regression tree methodology

    Mathematics, Vol. 8, Núm. 6

  2. Chrome Layer Thickness Modelling in a Hard Chromium Plating Process Using a Hybrid PSO/ RBF–SVM–Based Model

    IJIMAI, Vol. 6, Núm. 4, pp. 39-48

  3. Directional Attenuation Relationship for Ground Vibrations Induced by Mine Tremors

    Journal of Mining Science, Vol. 56, Núm. 2, pp. 236-245

  4. Predicting benzene concentration using machine learning and time series algorithms

    Mathematics, Vol. 8, Núm. 12, pp. 1-21

  5. Sustainable earthworks: Optimization with the ICOM method

    Energy Reports, Vol. 6, pp. 404-419

2019

  1. Multivariate analysis to relate CTOD values with material properties in steel welded joints for the offshore wind power industry

    Energies, Vol. 12, Núm. 20

  2. Predictive modelling of the higher heating value in biomass torrefaction for the energy treatment process using machine-learning techniques

    Neural Computing and Applications, Vol. 31, Núm. 12, pp. 8823-8836

2018

  1. Air Quality Modeling Using the PSO-SVM-Based Approach, MLP Neural Network, and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

    Environmental Modeling and Assessment, Vol. 23, Núm. 3, pp. 229-247

2017

  1. Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions

    Journal of Computational and Applied Mathematics, Vol. 311, pp. 704-717

  2. Predicting changes in induced seismicity on the basis of estimated rock mass energy states

    International Journal of Rock Mechanics and Mining Sciences, Vol. 95, pp. 79-86

2016

  1. A new predictive model based on the abc optimized multivariate adaptive regression splines approach for predicting the remaining useful life in aircraft engines

    Energies, Vol. 9, Núm. 6

  2. Hard-rock stability analysis for span design in entry-type excavations with learning classifiers

    Materials, Vol. 9, Núm. 7

  3. Hybrid ABC optimized MARS-based modeling of the milling tool wear from milling run experimental data

    Materials, Vol. 9, Núm. 2

2013

  1. Forecasting SO2 pollution incidents by means of Elman artificial neural networks and ARIMA models

    Abstract and Applied Analysis, Vol. 2013