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2020 – today
- 2023
[j57]Dalil Hadjout
, Abderrazak Sebaa, José F. Torres, Francisco Martínez-Álvarez:
Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market. Expert Syst. Appl. 227: 120123 (2023)- [j56]A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso:
A new approach based on association rules to add explainability to time series forecasting models. Inf. Fusion 94: 169-180 (2023) - [j55]M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
PHILNet: A novel efficient approach for time series forecasting using deep learning. Inf. Sci. 632: 815-832 (2023) - [j54]Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting. J. Big Data 10(1): 80 (2023) - [j53]Antonio M. Fernández-Gómez, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
A new Apache Spark-based framework for big data streaming forecasting in IoT networks. J. Supercomput. 79(10): 11078-11100 (2023) - [c53]E. Tefera, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez:
A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia. HAIS 2023: 207-218 - [c52]Angela Troncoso-García, Alicia Troncoso Lora, Francisco Martínez-Álvarez, María Martínez-Ballesteros:
Evolutionary computation to explain deep learning models for time series forecasting. SAC 2023: 433-436 - [c51]Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal. SAC 2023: 441-448 - [c50]Andrés Manuel Chacón-Maldonado, A. R. Troncoso-García, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, A. Troncoso:
Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning. SOCO (2) 2023: 121-131 - [c49]M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
Explaining Learned Patterns in Deep Learning by Association Rules Mining. SOCO (2) 2023: 132-141 - [c48]Pablo Casas-Gómez, Francisco Martínez-Álvarez, Alicia Troncoso, Juan Carlos Linares:
Machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment. SOCO (1) 2023: 229-238 - [e10]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez-Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado:
International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022) - Proceedings, Salamanca, Spain, 5-7 September. Lecture Notes in Networks and Systems 532, Springer 2023, ISBN 978-3-031-18408-6 [contents] - [e9]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez-Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luís Calvo-Rolle, Héctor Quintián, Emilio Corchado:
International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023) - Proceedings, Salamanca, Spain, 5-7 September, 2023. Lecture Notes in Networks and Systems 748, Springer 2023, ISBN 978-3-031-42518-9 [contents] - [e8]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez-Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luís Calvo-Rolle, Héctor Quintián, Emilio Corchado:
Hybrid Artificial Intelligent Systems - 18th International Conference, HAIS 2023, Salamanca, Spain, September 5-7, 2023, Proceedings. Lecture Notes in Computer Science 14001, Springer 2023, ISBN 978-3-031-40724-6 [contents] - [e7]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez-Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio S. Corchado Rodríguez:
17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) - Salamanca, Spain, September 5-7, 2022, Proceedings. Lecture Notes in Networks and Systems 531, Springer 2023, ISBN 978-3-031-18049-1 [contents] - [e6]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez-Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luís Calvo-Rolle, Héctor Quintián, Emilio Corchado:
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) - Salamanca, Spain, September 5-7, 2023, Proceedings, Volume 1. Lecture Notes in Networks and Systems 749, Springer 2023, ISBN 978-3-031-42528-8 [contents] - [e5]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez-Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luís Calvo-Rolle, Héctor Quintián, Emilio Corchado:
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) - Salamanca, Spain, September 5-7, 2023, Proceedings, Volume 2. Lecture Notes in Networks and Systems 750, Springer 2023, ISBN 978-3-031-42535-6 [contents] - 2022
- [j52]Kien-Trinh Thi Bui, José F. Torres, David Gutiérrez-Avilés, Viet-Ha Nhu, Dieu Tien Bui, Francisco Martínez-Álvarez:
Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm. Comput. Aided Civ. Infrastructure Eng. 37(11): 1368-1386 (2022) - [j51]Francisco Martínez-Álvarez, Alicia Troncoso Lora, Héctor Quintián, Emilio Corchado:
Special issue SOCO 2019: New trends in soft computing and its application in industrial and environmental problems. Neurocomputing 470: 278-279 (2022) - [j50]Laura Melgar-García, David Gutiérrez-Avilés, Maria Teresa Godinho, Rita Espada, Isabel Sofia Brito, Francisco Martínez-Álvarez, Alicia Troncoso, Cristina Rubio-Escudero:
A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture. Neurocomputing 500: 268-278 (2022) - [j49]Miguel Angel Molina-Cabanillas, M. J. Jiménez-Navarro, Ricardo Arjona, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting. Knowl. Based Syst. 254: 109644 (2022) - [j48]José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso:
A deep LSTM network for the Spanish electricity consumption forecasting. Neural Comput. Appl. 34(13): 10533-10545 (2022) - [c47]Andrés Manuel Chacón-Maldonado, Miguel Angel Molina-Cabanillas, Alicia Troncoso, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning. HAIS 2022: 274-285 - [c46]A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso:
Explainable machine learning for sleep apnea prediction. KES 2022: 2930-2939 - [c45]C. Segarra-Martín, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez:
A novel approach to discover numerical association based on the coronavirus optimization algorithm. SAC 2022: 1148-1151 - [c44]Juan Alberto Gallardo-Gómez, Federico Divina, Alicia Troncoso, Francisco Martínez-Álvarez:
Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem. SOCO 2022: 413-422 - [c43]Ejigu T. Habtermariam, Kula Kekeba, Alicia Troncoso, Francisco Martínez-Álvarez:
A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia. SOCO 2022: 423-432 - [c42]Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Sousa Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection. SOCO 2022: 557-566 - [e4]Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez-Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado:
Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Salamanca, Spain, September 5-7, 2022, Proceedings. Lecture Notes in Computer Science 13469, Springer 2022, ISBN 978-3-031-15470-6 [contents] - 2021
- [j47]Aythami Morales, Francisco Martínez-Álvarez, Russell L. Woods:
Saccade Landing Point Prediction Based on Fine-Grained Learning Method. IEEE Access 9: 52474-52484 (2021) - [j46]José F. Torres, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, Alicia Troncoso:
Deep Learning for Time Series Forecasting: A Survey. Big Data 9(1): 3-21 (2021) - [j45]Antonio Morales-Esteban, Francisco Martínez-Álvarez, Sanja Scitovski, Rudolf Scitovski:
Mahalanobis clustering for the determination of incidence-magnitude seismic parameters for the Iberian Peninsula and the Republic of Croatia. Comput. Geosci. 156: 104873 (2021) - [c41]José F. Torres, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso:
Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks. CAEPIA 2021: 216-225 - [c40]M. Á. Molina, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés:
A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery. HAIS 2021: 511-523 - [c39]A. Melara, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez:
Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning. SOCO 2021: 665-674 - [c38]M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso, Gualberto Asencio-Cortés:
HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting. SOCO 2021: 717-727 - [c37]Dalil Hadjout, José F. Torres, Abderrazak Sebaa, Francisco Martínez-Álvarez:
Medium-Term Electricity Consumption Forecasting in Algeria Based on Clustering, Deep Learning and Bayesian Optimization Methods. SOCO 2021: 739-748 - 2020
- [j44]Francisco Martínez-Álvarez, Pedro J. Zufiria, Luis J. Yebra:
Port-Hamiltonian Modeling of Multiphysics Systems and Object-Oriented Implementation With the Modelica Language. IEEE Access 8: 105980-105996 (2020) - [j43]Antonio M. Fernández, David Gutiérrez-Avilés, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration. Big Data Res. 19-20: 100135 (2020) - [j42]Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, José F. Torres, David Gutiérrez-Avilés, Laura Melgar-García, Rubén Pérez-Chacón, Cristina Rubio-Escudero, José C. Riquelme, Alicia Troncoso Lora:
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model. Big Data 8(4): 308-322 (2020) - [j41]Guillermo Santamaría Bonfil, María-Blanca Ibáñez-Espiga, Miguel Pérez-Ramírez, Gustavo Arroyo-Figueroa, Francisco Martínez-Álvarez:
Learning analytics for student modeling in virtual reality training systems: Lineworkers case. Comput. Educ. 151: 103871 (2020) - [j40]Rubén Pérez-Chacón, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Alicia Troncoso Lora:
Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand. Inf. Sci. 540: 160-174 (2020) - [j39]Francisco Martínez-Álvarez, Dieu Tien Bui:
Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management. Remote. Sens. 12(2): 301 (2020) - [j38]Fateme Moslehi, Abdorrahman Haeri, Francisco Martínez-Álvarez:
A novel hybrid GA-PSO framework for mining quantitative association rules. Soft Comput. 24(6): 4645-4666 (2020) - [c36]Oihana Mitxelena-Hoyos, José Lázaro Amaro-Mellado, Francisco Martínez-Álvarez:
Use of IT in Project-Based Learning Applied to the Subject Surveying in Civil Engineering. ICEUTE 2020: 428-437 - [c35]Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme:
On the Performance of Deep Learning Models for Time Series Classification in Streaming. SOCO 2020: 144-154 - [c34]Laura Melgar-García, Maria Teresa Godinho, Rita Espada, David Gutiérrez-Avilés, Isabel Sofia Brito, Francisco Martínez-Álvarez, Alicia Troncoso, Cristina Rubio-Escudero:
Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering. SOCO 2020: 226-236 - [c33]Miguel Ángel Molina, Gualberto Asencio-Cortés, José C. Riquelme, Francisco Martínez-Álvarez:
A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets. SOCO 2020: 741-750 - [e3]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José António Sáez Muñoz, Héctor Quintián, Emilio Corchado:
International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) - Seville, Spain, May 13-15, 2019, Proceedings. Advances in Intelligent Systems and Computing 951, Springer 2020, ISBN 978-3-030-20004-6 [contents] - [e2]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José António Sáez Muñoz, Héctor Quintián, Emilio Corchado:
14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) - Seville, Spain, May 13-15, 2019, Proceedings. Advances in Intelligent Systems and Computing 950, Springer 2020, ISBN 978-3-030-20054-1 [contents] - [i2]Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme:
On the performance of deep learning models for time series classification in streaming. CoRR abs/2003.02544 (2020) - [i1]Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, José F. Torres, David Gutiérrez-Avilés, Laura Melgar-García, Rubén Pérez-Chacón, Cristina Rubio-Escudero, José C. Riquelme, Alicia Troncoso:
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model. CoRR abs/2003.13633 (2020)
2010 – 2019
- 2019
- [j37]Catalina Gomez-Quiles, Gualberto Asencio-Cortés, Adolfo Gastalver-Rubio, Francisco Martínez-Álvarez, Alicia Troncoso, Joan Manresa, José C. Riquelme, Jesús Manuel Riquelme-Santos:
A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System. IEEE Access 7: 120840-120856 (2019) - [j36]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Big data solar power forecasting based on deep learning and multiple data sources. Expert Syst. J. Knowl. Eng. 36(4) (2019) - [j35]Francisco Martínez-Álvarez, A. Morales-Esteban:
Big data and natural disasters: New approaches for spatial and temporal massive data analysis. Comput. Geosci. 129: 38-39 (2019) - [j34]Francisco Martínez-Álvarez, Alicia Troncoso, Héctor Quintián, Emilio Corchado:
Special issue on Hybrid Artificial Intelligence Systems from HAIS 2016 Conference. Neurocomputing 353: 1-2 (2019) - [j33]Ricardo L. Talavera-Llames, Rubén Pérez-Chacón, Alicia Troncoso, Francisco Martínez-Álvarez:
MV-kWNN: A novel multivariate and multi-output weighted nearest neighbours algorithm for big data time series forecasting. Neurocomputing 353: 56-73 (2019) - [j32]Antonio Galicia, Ricardo L. Talavera-Llames, Alicia Troncoso Lora, Irena Koprinska, Francisco Martínez-Álvarez:
Multi-step forecasting for big data time series based on ensemble learning. Knowl. Based Syst. 163: 830-841 (2019) - [c32]Miguel García-Torres, David Becerra-Alonso, Francisco Antonio Gómez Vela, Federico Divina, Isabel López-Cobo, Francisco Martínez-Álvarez:
Analysis of Student Achievement Scores: A Machine Learning Approach. CISIS-ICEUTE 2019: 275-284 - [c31]José Lázaro Amaro-Mellado, Daniel Antón, Macarena Pérez-Suárez, Francisco Martínez-Álvarez:
Game-Based Student Response System Applied to a Multidisciplinary Teaching Context. CISIS-ICEUTE 2019: 329-339 - [c30]Cristina Rubio-Escudero, Francisco Martínez-Álvarez, E. Atencia-Gil, Alicia Troncoso:
Implementation of an Internal Quality Assurance System at Pablo de Olavide University of Seville: Improving Computer Science Students Skills. CISIS-ICEUTE 2019: 340-348 - [c29]José F. Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting. IWANN (1) 2019: 259-269 - [c28]Antonio M. Fernández, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks. SOCO 2019: 91-100 - 2018
- [j31]José L. Amaro-Mellado, Antonio Morales-Esteban, Francisco Martínez-Álvarez:
Mapping of seismic parameters of the Iberian Peninsula by means of a geographic information system. Central Eur. J. Oper. Res. 26(3): 739-758 (2018) - [j30]Álvaro Gómez-Losada, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, José C. Riquelme:
A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information. Environ. Model. Softw. 110: 52-61 (2018) - [j29]Emilio Florido, Gualberto Asencio-Cortés, José Luis Aznarte, Cristina Rubio-Escudero, Francisco Martínez-Álvarez:
A novel tree-based algorithm to discover seismic patterns in earthquake catalogs. Comput. Geosci. 115: 96-104 (2018) - [j28]Gualberto Asencio-Cortés, Antonio Morales-Esteban, Xueyi Shang, Francisco Martínez-Álvarez:
Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure. Comput. Geosci. 115: 198-210 (2018) - [j27]José F. Torres, Antonio Galicia, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
A scalable approach based on deep learning for big data time series forecasting. Integr. Comput. Aided Eng. 25(4): 335-348 (2018) - [j26]Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso Lora:
A novel spark-based multi-step forecasting algorithm for big data time series. Inf. Sci. 467: 800-818 (2018) - [j25]Ricardo L. Talavera-Llames, Rubén Pérez-Chacón, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Big data time series forecasting based on nearest neighbours distributed computing with Spark. Knowl. Based Syst. 161: 12-25 (2018) - [j24]Neeraj Bokde, Marcus W. Beck, Francisco Martínez-Álvarez, Kishore Kulat:
A novel imputation methodology for time series based on pattern sequence forecasting. Pattern Recognit. Lett. 116: 88-96 (2018) - [c27]David Gutiérrez-Avilés, J. A. Fábregas, J. Tejedor, Francisco Martínez-Álvarez, Alicia Troncoso, A. Arcos, José C. Riquelme:
SmartFD: A Real Big Data Application for Electrical Fraud Detection. HAIS 2018: 120-130 - [c26]Zheng Wang, Irena Koprinska, Alicia Troncoso, Francisco Martínez-Álvarez:
Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting. IJCNN 2018: 1-8 - [c25]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Deep Learning for Big Data Time Series Forecasting Applied to Solar Power. SOCO-CISIS-ICEUTE 2018: 123-133 - [c24]Cristina Rubio-Escudero, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme:
Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses. SOCO-CISIS-ICEUTE 2018: 553-561 - 2017
- [j23]Francisco Martínez-Álvarez, Alicia Troncoso, Jorge Reyes, María Martínez-Ballesteros, José C. Riquelme:
Applications of Computational Intelligence in Time Series. Comput. Intell. Neurosci. 2017: 9361749:1-9361749:2 (2017) - [j22]Gualberto Asencio-Cortés, Sanja Scitovski, Rudolf Scitovski, Francisco Martínez-Álvarez:
Temporal analysis of croatian seismogenic zones to improve earthquake magnitude prediction. Earth Sci. Informatics 10(3): 303-320 (2017) - [j21]Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, A. Morales-Esteban, Jorge Reyes, Alicia Troncoso Lora:
Using principal component analysis to improve earthquake magnitude prediction in Japan. Log. J. IGPL 25(6): 949-966 (2017) - [j20]Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Alicia Troncoso Lora, A. Morales-Esteban:
Medium-large earthquake magnitude prediction in Tokyo with artificial neural networks. Neural Comput. Appl. 28(5): 1043-1055 (2017) - [j19]Neeraj Bokde, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Kishore Kulat:
PSF: Introduction to R Package for Pattern Sequence Based Forecasting Algorithm. R J. 9(1): 324 (2017) - [c23]Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso:
Scalable Forecasting Techniques Applied to Big Electricity Time Series. IWANN (2) 2017: 165-175 - [c22]José F. Torres, Antonio M. Fernández, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load. IWINAC (2) 2017: 203-212 - 2016
- [j18]María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez, José C. Riquelme:
Obtaining optimal quality measures for quantitative association rules. Neurocomputing 176: 36-47 (2016) - [j17]María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme:
Improving a multi-objective evolutionary algorithm to discover quantitative association rules. Knowl. Inf. Syst. 49(2): 481-509 (2016) - [j16]Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, A. Morales-Esteban, Jorge Reyes:
A sensitivity study of seismicity indicators in supervised learning to improve earthquake prediction. Knowl. Based Syst. 101: 15-30 (2016) - [j15]Gualberto Asencio-Cortés, Emilio Florido, Alicia Troncoso, Francisco Martínez-Álvarez:
A novel methodology to predict urban traffic congestion with ensemble learning. Soft Comput. 20(11): 4205-4216 (2016) - [c21]Antonio M. Fernández, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez:
Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration. CAEPIA 2016: 150-159 - [c20]Rubén Pérez-Chacón, Ricardo L. Talavera-Llames, Francisco Martínez-Álvarez, Alicia Troncoso Lora:
Finding Electric Energy Consumption Patterns in Big Time Series Data. DCAI 2016: 231-238 - [c19]Khawaja M. Asim, Adnan Idris, Francisco Martínez-Álvarez, Talat Iqbal:
Short Term Earthquake Prediction in Hindukush Region Using Tree Based Ensemble Learning. FIT 2016: 365-370 - [c18]Ricardo L. Talavera-Llames, Rubén Pérez-Chacón, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez:
A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting. HAIS 2016: 174-185 - [c17]Fawad Hassan, Naeem Iqbal, Francisco Martínez-Álvarez, Khawaja M. Asim:
Passivity Based Control of Cyber Physical Systems Under Zero-Dynamics Attack. HAIS 2016: 634-646 - [e1]Francisco Martínez-Álvarez, Alicia Troncoso, Héctor Quintián, Emilio Corchado:
Hybrid Artificial Intelligent Systems - 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings. Lecture Notes in Computer Science 9648, Springer 2016, ISBN 978-3-319-32033-5 [contents] - 2015
- [j14]Francisco Martínez-Álvarez, David Gutiérrez-Avilés, Antonio Morales-Esteban, Jorge Reyes, José L. Amaro-Mellado, Cristina Rubio-Escudero:
A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula. Entropy 17(7): 5000-5021 (2015) - [j13]Emilio Florido, Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, José Luis Aznarte-Mellado:
Detecting precursory patterns to enhance earthquake prediction in Chile. Comput. Geosci. 76: 112-120 (2015) - [j12]Jorge García-Gutiérrez, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables. Neurocomputing 167: 24-31 (2015) - [c16]Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, Alicia Troncoso Lora:
Improving Earthquake Prediction with Principal Component Analysis: Application to Chile. HAIS 2015: 393-404 - [c15]Emilio Florido, O. Castaño, Alicia Troncoso, Francisco Martínez-Álvarez:
Data Mining for Predicting Traffic Congestion and Its Application to Spanish Data. SOCO 2015: 341-351 - 2014
- [j11]Antonio Morales-Esteban, Francisco Martínez-Álvarez, Sanja Scitovski, Rudolf Scitovski:
A fast partitioning algorithm using adaptive Mahalanobis clustering with application to seismic zoning. Comput. Geosci. 73: 132-141 (2014) - [j10]María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
Selecting the best measures to discover quantitative association rules. Neurocomputing 126: 3-14 (2014) - [j9]David Gutiérrez-Avilés, Cristina Rubio-Escudero, Francisco Martínez-Álvarez, José C. Riquelme:
TriGen: A genetic algorithm to mine triclusters in temporal gene expression data. Neurocomputing 132: 42-53 (2014) - 2013
- [j8]Jorge Reyes, A. Morales-Esteban, Francisco Martínez-Álvarez:
Neural networks to predict earthquakes in Chile. Appl. Soft Comput. 13(2): 1314-1328 (2013) - [j7]Francisco Martínez-Álvarez, Jorge Reyes, A. Morales-Esteban, Cristina Rubio-Escudero:
Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula. Knowl. Based Syst. 50: 198-210 (2013) - [c14]María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules. HAIS 2013: 578-587 - [c13]