Artículos en revista

Año 2021

  • A.M. Gómez-Orellana, J.C. Fernández, M. Dorado-Moreno, P.A. Gutiérrez y C. Hervás-Martínez. "Building Suitable Datasets for Soft Computing and Machine Learning Techniques from Meteorological Data Integration: A Case Study for Predicting Significant Wave Height and Energy Flux", Energies, Vol. 14(2). 2021, pp. 468. JCR(2019): 2.702 Position: 63/112 (Q3) Category: ENERGY & FUELS.
  • Á. Carmona-Poyato, N.L. Fernández-García, F.J. Madrid-Cuevas y A.M. Durán-Rosal. "A new approach for optimal offline time-series segmentation with error bound guarantee", Pattern Recognition, Vol. In Press. 2021. JCR(2019): 7.196 Position: 12/137 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.
  • B. Amiri, A.M. Gómez-Orellana, P.A. Gutiérrez, R. Dizene, C. Hervás-Martínez y K. Dahmani. "A Novel Approach for Global Solar Irradiation Forecasting on Tilted Plane using Hybrid Evolutionary Neural Networks", Journal of Cleaner Production, Vol. 287, March, 2021, pp. 125577. JCR(2019): 7.246 Position: 19/265 (Q1) Category: ENVIRONMENTAL SCIENCES.

Año 2020

  • D. Guijo-Rubio, C. Casanova-Mateo, J. Sanz-Justo, P.A. Gutiérrez, S. Cornejo-Bueno, C. Hervás-Martínez y S. Salcedo-Sanz. "Ordinal regression algorithms for the analysis of convective situations over Madrid-Barajas airport", Atmospheric Research, Vol. 236, May, 2020, pp. 104798. JCR(2018): 4.114 Position: 13/86 (Q1) Category: METEOROLOGY & ATMOSPHERIC SCIENCES. http://doi.org/10.1016/j.atmosres.2019.104798
  • M. Dorado-Moreno, N. Navarin, P.A. Gutiérrez, L. Prieto, A. Sperduti, S. Salcedo-Sanz y C. Hervás-Martínez. "Multi-task learning for the prediction of wind power ramp events with deep neural networks", Neural Networks, Vol. 123, March, 2020, pp. 401-411. JCR(2018): 5.785 Position: 16/134 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.neunet.2019.12.017
  • A. Rivero-Juárez, D. Guijo-Rubio, F. Téllez, R. Palacios, D. Merino, J. Macías, J.C. Fernández, P.A. Gutiérrez, A. Rivero y C. Hervás-Martínez. "Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals", PLoS One. 2020. JCR(2018): 2.776 Position: 24/69 (Q2) Category: MULTIDISCIPLINARY SCIENCES. http://doi.org/10.1371/journal.pone.0227188
  • D. Guijo-Rubio, A.M. Durán-Rosal, P.A. Gutiérrez, A. Troncoso y C. Hervás-Martínez. "Time series clustering based on the characterisation of segment typologies", IEEE Transactions on Cybernetics, Vol. Accepted on 22th December 2019. 2020. JCR(2018): 10.387 Position: 4/134 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1109/TCYB.2019.2962584
  • • D. Guijo-Rubio, A.M. Gómez-Orellana, P.A. Gutiérrez y C. Hervás-Martínez. "Short- and long-term energy flux prediction using Multi-Task Evolutionary Artificial Neural Networks", Ocean Engineering, Vol. 216, 108089, 2020. JCR(2019): 3.068 Position: 1/14 (Q1) Category: MARINE ENGINEERING.
    • D. Guijo-Rubio, P.A. Gutiérrez, C. Casanova-Mateo, J.C. Fernández, A.M. Gómez-Orellana, P. Salvador-González, S. Salcedo-Sanz y C. Hervás-Martínez. "Prediction of convective clouds formation using evolutionary neural computation techniques", Neural Computing and Applications, Vol. 32(13917-1392), February, 2020. JCR(2019): 4.774 Position: 23/136 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.
    • F.J. Jiménez-Romero, D. Guijo-Rubio, F.R. Lara-Raya, A. Ruiz-González y C. Hervás-Martínez. "Validation of artificial neural networks to model the acoustic behaviour of induction motors", Applied Acoustics, Vol. 166, March, 2020, pp. 107332. JCR(2019): 2.440 Position: 9/32 (Q2) Category: ACOUSTICS.
    • A. Martín, V.M. Vargas-Yun, P.A. Gutiérrez, D. Camacho y C. Hervás-Martínez. "Optimising Convolutional Neural Networks using a Hybrid Statistically-driven Coral Reef Optimisation algorithm", Applied Soft Computing, Vol. 90, May, 2020, pp. 106144. JCR(2019): 5.472 Position: 9/109 (Q1) Category: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS.
    • C. Castillo-Botón, D. Casillas-Pérez, C. Casanova-Mateo, L.M. Moreno-Saavedra, B. Morales-Díaz, J. Sanz-Justo, P.A. Gutiérrez y S. Salcedo-Sanz. "Analysis and Prediction of Dammed Water Level in a Hydropower Reservoir Using Machine Learning and Persistence-Based Techniques", Water, Vol. 12(6), May, 2020, pp. 1528. JCR(2019): 2.544 Position: 31/94 (Q2) Category: WATER RESOURCES – SCIE.
    • Á. Carmona-Poyato, N.L. Fernández-García, F.J. Madrid-Cuevas y A.M. Durán-Rosal. "A new approach for optimal time-series segmentation", Pattern Recognition Letters, Vol. 135, July, 2020, pp. 153-159. JCR(2019): 3.255 Position: 43/136 (Q2) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.
    • V.M. Vargas-Yun, P.A. Gutiérrez y C. Hervás-Martínez. "Cumulative link models for deep ordinal classification", Neurocomputing, Vol. 401, August, 2020, pp. 48-58. JCR(2019): 4.438 Position: 28/136 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.
    • D. Guijo-Rubio, P.A. Gutiérrez y C. Hervás-Martínez. "Machine learning methods in organ transplantation", Current Opinion in Organ Transplantation, Vol. 25(4), August, 2020, pp. 399-405. JCR(2019): 2.571 Position: 13/24 (Q3) Category: TRANSPLANTATION.
    • D. Guijo-Rubio, A.M. Durán-Rosal, P.A. Gutiérrez, A.M. Gómez-Orellana, C. Casanova-Mateo, J. Sanz-Justo, S. Salcedo-Sanz y C. Hervás-Martínez. "Evolutionary artificial neural networks for accurate solar radiation prediction", Energy, Vol. 210, November, 2020, pp. 1-11. JCR(2019): 6.082 Position: 3/61 (Q1) Category: THERMODYNAMICS.
    • M. Dorado-Moreno, P.A. Gutiérrez, L. Cornejo-Bueno, L. Prieto, S. Salcedo-Sanz y C. Hervás-Martínez. "Ordinal multi-class architecture for predicting wind power ramp events based on reservoir computing", Neural Processing Letters, Vol. 52(3), December, 2020, pp. 57-74. JCR(2019): 2.891 Position: 53/136 (Q2) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.

Año 2019

  • C. Perales-González, M. Carbonero-Ruz, D. Becerra-Alonso, J. Pérez-Rodríguez y F. Fernandez-Navarro. "Regularized ensemble neural networks models in the Extreme Learning Machine framework", Neurocomputing, Vol. 361, October, 2019, pp. 196-211. JCR(2018): 4.072 Position: 28/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.neucom.2019.06.040
  • M.C. Heredia-Gómez, S. García, P.A. Gutiérrez y F. Herrera. "OCAPIS: R package for Ordinal Classification and Preprocessing in Scala", Progress in Artificial Intelligence, Vol. 8, September, 2019, pp. 287-292. http://doi.org/10.1007/s13748-019-00175-1
  • A.M. Durán-Rosal, P.A. Gutiérrez, Á. Carmona-Poyato y C. Hervás-Martínez. "A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation", Neurocomputing, Vol. 353, August, 2019, pp. 45-55. JCR(2018): 4.072 Position: 28/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.neucom.2018.05.129
  • A.M. Durán-Rosal, P.A. Gutiérrez, S. Salcedo-Sanz y C. Hervás-Martínez. "Dynamical Memetization in Coral Reef Optimization Algorithms for Optimal Time Series Approximation", Progress in Artificial Intelligence, Vol. 8, June, 2019, pp. 253-262. http://doi.org/10.1007/s13748-019-00176-0
  • J.-R. Cano, P.A. Gutiérrez, B. Krawczyk, M. Wozniak y S. García. "Monotonic classification: An overview on algorithms, performance measures and data sets", Neurocomputing, Vol. 341, May, 2019, pp. 168-182. JCR(2018): 4.072 Position: 28/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.neucom.2019.02.024
  • M. Valverde-Moreno, M. Torres-Jiménez, A.M. Lucia-Casademunt y Y. Muñoz-Ocaña. "Cross cultural analysis of direct employee participation: dealing with gender and cultural values", Frontiers in Psychology, Vol. 10, April, 2019, pp. 1-13. JCR(2018): 2.129 Position: 40/137 (Q2) Category: PSYCHOLOGY, MULTIDISCIPLINARY. http://doi.org/10.3389/fpsyg.2019.00723
  • M. Pérez-Ortiz, A.M. Durán-Rosal, P.A. Gutiérrez, J. Sánchez-Monedero, A. Nikolaou, F. Fernandez-Navarro y C. Hervás-Martínez. "On the use of evolutionary time series analysis for segmenting paleoclimate data", Neurocomputing, Vol. 326-327, January, 2019, pp. 3-14. JCR(2018): 4.072 Position: 28/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.neucom.2016.11.101
  • J. Sánchez-Monedero, P.A. Gutiérrez y M. Pérez-Ortiz. "ORCA: A Matlab/Octave Toolbox for Ordinal Regression", Journal of Machine Learning Research, Vol. 20. 2019, pp. 1-5. JCR(2018): 4.091 Position: 27/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE.
  • F. Comino, D. Guijo-Rubio, M. R. de Adana y C. Hervás-Martínez. "Validation of multitask artificial neural networks to model desiccant wheels activated at low temperature", International Journal of Refrigeration, Vol. 100. 2019, pp. 434-442. JCR(2018): 3.177 Position: 23/129 (Q1) Category: THERMODYNAMICS. http://doi.org/10.1016/j.ijrefrig.2019.02.002
  • J.C. Fernández, M. Carbonero-Ruz, P.A. Gutiérrez y C. Hervás-Martínez. "Multi-objective evolutionary optimization using the relationship between F1 and accuracy metrics in classification tasks", Applied Intelligence, Vol. 49. 2019, pp. 3447-3463. JCR(2018): 2.882 Position: 46/133 (Q2) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1007/s10489-019-01447-y
  • S. Jiménez-Fernández, C. Camacho-Gómez, R. Mallol-Poyato, J.C. Fernández, J.D. Ser, A. Portilla-Figueras y S. Salcedo-Sanz. "Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm", Sustainability, Vol. 11. 2019, pp. 169. JCR(2018): 2.592 Position: 44/116 (Q2) Category: ENVIRONMENTAL STUDIES. http://doi.org/10.3390/su11010169
  • M. Dorado-Moreno, P.A. Gutiérrez, L. Cornejo-Bueno, L. Prieto, S. Salcedo-Sanz y C. Hervás-Martínez. "Ordinal multi-class architecture for predicting wind power ramp events based on reservoir computing", Neural Processing Letters, Vol. Accepted on 2018/09/19. 2019. JCR(2018): 2.591 Position: 59/133 (Q2) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1007/s11063-018-9922-5

Año 2018

  • A.M. Durán-Rosal, J.C. Fernández, C. Casanova-Mateo, J. Sanz-Justo, S. Salcedo-Sanz y C. Hervás-Martínez. "Efficient Fog Prediction with Multi-objective Evolutionary Neural Networks", Applied Soft Computing, Vol. 70, September, 2018, pp. 347-358. JCR(2018): 4.873 Position: 20/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.asoc.2018.05.035
  • J.C. Fernández, M. Cruz-Ramírez y C. Hervás-Martínez. "Sensitivity versus accuracy in ensemble models of Artificial Neural Networks from Multi-objective Evolutionary Algorithms", Neural Computing and Applications, Vol. 30, June, 2018, pp. 289-305. JCR(2018): 4.664 Position: 21/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://dx.doi.org/10.1007/s00521-016-2781-y
  • A.M. Durán-Rosal, P.A. Gutiérrez, F.J. Martínez-Estudillo y C. Hervás-Martínez. "Simultaneous optimisation of clustering quality and approximation error for time series segmentation", Information Sciences, Vol. 442-443, May, 2018, pp. 186-201. JCR(2018): 5.524 Position: 9/155 (Q1) Category: COMPUTER SCIENCE, INFORMATION SYSTEMS. http://doi.org/10.1016/j.ins.2018.02.041
  • J. Sánchez-Monedero, M. Pérez-Ortiz, A. Sáez, P.A. Gutiérrez y C. Hervás-Martínez. "Partial order label decomposition approaches for melanoma diagnosis", Applied Soft Computing, Vol. 64, March, 2018, pp. 341-355. JCR(2018): 4.873 Position: 11/106 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.asoc.2017.11.042
  • M.D. Ayllón, R. Ciria, M. Cruz-Ramírez, M. Pérez-Ortiz, I. Gómez, R. Valente, J. O’Grady, M. de la Mata, C. Hervás-Martínez, N.D. Heaton y J. Briceño. "Validation of artificial neural networks as a methodology for donor‐recipient matching for liver transplantation", Liver Transplantation, Vol. 24, February, 2018, pp. 192-203. JCR(2018): 4.159 Position: 16/203 (Q1) Category: SURGERY. http://doi.org/10.1002/lt.24870
  • F. Fernandez-Navarro, M. A. de la Cruz, P.A. Gutiérrez, A. Castaño-Méndez y C. Hervás-Martínez. "Time series forecasting by recurrent product unit neural networks", Neural Computing and Applications, Vol. 29, February, 2018, pp. 779-791. JCR(2018): 4.664 Position: 21/133 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://dx.doi.org/10.1007/s00521-016-2494-2
  • A. García-Jurado, P. Castro-González, M. Torres-Jiménez y A. Leal-Rodriguez. "Valuating the role of Gamification and Flow in e-consumers: Millennials versus Generation X", Kybernetes, Vol. 48. 2018, pp. 1278-1300. JCR(2018): 1.381 Position: 14/23 (Q3) Category: COMPUTER SCIENCE, CYBERNETICS. http://doi.org/10.1108/K-07-2018-0350
  • R. Cruz, K. Fernandes, J.F. Pinto-Costa, M. Pérez-Ortiz y J.S. Cardoso. "Binary Ranking for Ordinal Class Imbalance", Pattern Analysis and Applications, Vol. Accepted on 30th March 2018. 2018. JCR(2018): 1.410 Position: 92/133 (Q3) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1007/s10044-018-0705-4
  • A.M. Durán-Rosal, P.A. Gutiérrez, S. Salcedo-Sanz y C. Hervás-Martínez. "A statistically-driven Coral Reef Optimization algorithm for optimal size reduction of time series", Applied Soft Computing, Vol. 63. 2018, pp. 139-153. JCR(2018): 4.873 Position: 11/106 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. http://doi.org/10.1016/j.asoc.2017.11.037
  • M.D. Redel-Macías, C. Hervás-Martínez, P.A. Gutiérrez, S. Pinzi, A.J. Cubero-Atienza y M.P. Dorado. "Computational models to predict noise emissions of a diesel engine fueled with saturated and monounsaturated fatty acid methyl esters", Energy, Vol. 144. 2018, pp. 110-119. JCR(2018): 5.537 Position: 3/60 (Q1) Category: THERMODYNAMICS. http://doi.org/10.1016/j.energy.2017.11.143
  • D. Guijo-Rubio, P.A. Gutiérrez, C. Casanova-Mateo, J. Sanz-Justo, S. Salcedo-Sanz y C. Hervás-Martínez. "Prediction of low-visibility events due to fog using ordinal classification", Atmospheric Research, Vol. 214, Diciembre, 2018, pp. 64-73. JCR(2018): 4.114 Position: 13/86 (Q1) Category: METEOROLOGY & ATMOSPHERIC SCIENCES. http://doi.org/10.1016/j.atmosres.2018.07.017

Congresos

Año 2019

  • D. Guijo-Rubio, P.A. Gutiérrez y C. Hervás-Martínez. "Predicción de altura de ola mediante discretización basada en distribuciones utilizando clasificación ordinal". VII Congreso Cientı́fico de Investigadores en Formación. 2019. UCO.
  • D. Guijo-Rubio, P.J. Villalón-Vaquero, P.A. Gutiérrez, M.D. Ayllón, J. Briceño y C. Hervás-Martínez. "Modelling survival by machine learning methods in liver transplantation: application to the UNOS dataset". Proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2019). 14th-16th November. 2019. Manchester, UK. Lecture Notes in Computer Science (LNCS), vol. 11872. pp. 97-104. http://doi.org/10.1007/978-3-030-33617-2_11
  • D. Guijo-Rubio, P.A. Gutiérrez, R. Tavenard y A. Bagnall. "A hybrid approach to time series classification with shapelets". Proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2019). 14th-16th November. 2019. Manchester, UK. Lecture Notes in Computer Science (LNCS), vol. 11871. pp. 137-144. http://doi.org/10.1007/978-3-030-33607-3_16
    • http://doi.org/10.1109/ICCSRE.2019.8807613
  • V.M. Vargas-Yun, P.A. Gutiérrez y C. Hervás-Martínez. "Deep Ordinal Classification Based on the Proportional Odds Model". Proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC 2019). 3-7 junio. 2019. Almería (España). Lecture Notes in Computer Science (LNCS), vol. 11487. pp. 441-451. http://doi.org/10.1007/978-3-030-19651-6_43
  • M. Pérez-Ortiz, P. Tino, R. Mantiuk y C. Hervás-Martínez. "Exploiting synthetically generated data with semi-supervised learning for small and imbalanced datasets". Proceedings of the Thirty-Third AAAI (Association for the Advancement of Artificial Intelligence) Conference on Artificial Intelligence (AAAI'19). 27th February. 2019. Honolulu,Hawaii, USA. pp. 4715-4722. http://doi.org/10.1609/aaai.v33i01.33014715

Año 2018

  • A. Mikhailiuk, M. Pérez-Ortiz y R.K. Mantiuk. "Psychometric scaling of TID2013 dataset". International Conference on Quality of Multimedia Experience. 2018. http://doi.org/10.1109/QoMEX.2018.8463376
  • A.M. Durán-Rosal, P.A. Gutiérrez y C. Hervás-Martínez. "Detección y predicción de segmentos de altura de olas extremas". U. E. de Córdoba ed. 24th-26th January. 2018. Córdoba, Spain. Creando Redes Doctorales: La generación del conocimiento, vol. 6. pp. 509-512.
  • D. Guijo-Rubio, A.M. Durán-Rosal, P.A. Gutiérrez, A. Troncoso y C. Hervás-Martínez. "Time series clustering based on the characterisation of segment typologies". Proceedings of Third Bilbao Data Science Workshop (BiDAS 3). 8th-9th November. 2018. Bilbao (Spain).
  • A. Nikolaou, P.A. Gutiérrez, A.M. Durán-Rosal, F. Fernandez-Navarro, C. Hervás-Martínez y M. Pérez-Ortiz. "Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm". Proceedings of the 2018 European Planetary Science Congress. 16th-21st September. 2018. Berlin (Germany). EPSC2018-829-1, vol. 12. http://meetingorganizer.copernicus.org/EPSC2018/EPSC2018-829-1.pdf
  • D. Guijo-Rubio, A.M. Durán-Rosal, A. Gómez-Orellana, P.A. Gutiérrez y C. Hervás-Martínez. "Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction". Proceedings of the 2018 International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2018). 21st-23rd November. 2018. Madrid, Spain. Lecture Notes in Computer Science (LNCS), vol. 11315. pp. 171-179. http://doi.org/10.1007/978-3-030-03496-2_20
  • M. Dorado-Moreno, P.A. Gutiérrez, S. Salcedo-Sanz, L. Prieto y C. Hervás-Martínez. "Predicción ordinal de rampas de viento usando Echo State Networks de complejidad reducida". Proceedings of the 2018 Conference of the Spanish Association for Artificial Intelligence (CAEPIA2018). 23rd-26th October. 2018. Granada (Spain). pp. 132-138. http://sci2s.ugr.es/caepia18/proceedings/docs/CAEPIA2018_paper_88.pdf
  • M. Diaz-Lozano, D. Guijo-Rubio, P.A. Gutiérrez, C. Casanova-Mateo, S. Salcedo-Sanz y C. Hervás-Martínez. "Algoritmos de aprendizaje automático para predicción de niveles de niebla usando ventanas estáticas y dinámicas". Proceedings of the 2018 Conference of the Spanish Association for Artificial Intelligence (CAEPIA2018). 23rd-26th October. 2018. Granada (Spain). pp. 833-838. http://sci2s.ugr.es/caepia18/proceedings/docs/CAEPIA2018_paper_122.pdf
  • J. Camacho-Cañamón, M.-V. Guiote, A.-M. Santos-Bueno, E. Rodrı́guez-Cáceres, E. Carmona-Asenjo, J.-A. Vallejo-Casas, P.A. Gutiérrez y C. Hervás-Martínez. "Clasificación ordinal de los grados de afectación de la enfermedad de Parkinson empleando imágenes de transportadores presinápticos de dopamina". Proceedings of the 2018 Conference of the Spanish Association for Artificial Intelligence (CAEPIA2018). 23rd-26th October. 2018. Granada (Spain). pp. 167-172. http://sci2s.ugr.es/caepia18/proceedings/docs/CAEPIA2018_paper_111.pdf
  • A.M. Durán-Rosal, P.A. Gutiérrez, S. Salcedo-Sanz y C. Hervás-Martínez. "An Empirical Validation of a New Memetic CRO Algorithm for the Approximation of Time Series". Proceedings of the 2018 Conference of the Spanish Association for Artificial Intelligence (CAEPIA2018). 23rd-28th September. 2018. Granada (Spain). Lecture Notes in Computer Science, vol. 11160. pp. 209-218. http://doi.org/10.1007/978-3-030-00374-6_20
  • M. Dorado-Moreno, P.A. Gutiérrez, S. Salcedo-Sanz, L. Prieto y C. Hervás-Martínez. "Wind power ramp events ordinal prediction using minimum complexity echo state networks". Proceedings of the 2018 International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2018). 21st-23rd November. 2018. Madrid, Spain. Lecture Notes in Computer Science (LNCS), vol. 11315. pp. 180-187. http://doi.org/10.1007/978-3-030-03496-2_21
  • A.M. Durán-Rosal, D. Guijo-Rubio, P.A. Gutiérrez y C. Hervás-Martínez. "Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation". Bioinspired Optimization Methods and their Applications (BIOMA2018). 16th-18th May. 2018. Paris (France). Lecture Notes in Computer Science (LNCS), vol. 10835. pp. 126-137. http://doi.org/10.1007/978-3-030-03496-2_21
  • M. Pérez-Ortiz, P.A. Gutiérrez, P. Tino, C. Casanova-Mateo y S. Salcedo-Sanz. "A mixture of experts model for predicting persistent weather patterns". Proceedings of the 2018 IEEE International Joint Conference on Neural Networks (IJCNN 2018). 8th-13th July. 2018. Rio (Brazil). pp. 5714-5721. http://doi.org/10.1109/IJCNN.2018.8489179

Tesis doctorales

Año 2019

  • Doctorando: Manuel Dorado Moreno. “Predicción ordinal utilizando metodologías de aprendizaje automático: Aplicaciones”. Directores: C. Hervás-Martínez y P. A. Gutiérrez. Universidad de Córdoba. Fecha de lectura: 27/11/2019. Sobresaliente Cum Laude. Mención internacional.
  • Doctorando: Antonio Manuel Durán Rosal. “Minería de datos en series temporales: preprocesamiento, análisis, segmentación y predicción. Aplicaciones”. Directores: C. Hervás-Martínez y P. A. Gutiérrez. Universidad de Córdoba. Fecha de lectura: 17/05/2019. Sobresaliente Cum Laude. Mención internacional.
  • Doctorando: Alejandro García Jurado. “Enfoques Metodológicos para Medir el Efecto de la Gamificación en la Intención de Uso del Comercio Electrónico. Aplicación al Mercado Español”. Directores: C. Hervás-Martínez, P. Castro González y M. Torres Jiménez. Universidad de Córdoba. Fecha de lectura: 05/12/2019. Sobresaliente Cum Laude.

Año 2017

  • Doctoranda: M. Dolores Ayllón Terán. “Validación de las redes neuronales artificiales como metodología para la asignación donante-receptor en el trasplante hepático”. Directores: F.J. Briceño-Delgado y C. Hervás-Martínez. Universidad de Córdoba. Fecha de lectura: julio 2017. Sobresaliente Cum Laude.
  • Doctorando: Francisco de Borja Martín-Garrido. “Una aproximación a la relación entre los estilos de pensamiento y el grado de adaptación de los expatriados”. Directores: C.R. García Alonso, C. Vance, E. Morales. Universidad de Córdoba. Fecha de lectura: junio 2017. Sobresaliente Cum Laude. Mención internacional.
Universidad de Córdoba Universidad de Alcalá Ministerio de Ciencia, Innovación y Universidades Fondo Europeo de Desarrollo Regional