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ORCIDAlicia Troncoso Lora
Alicia Troncoso
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- affiliation: Pablo de Olavide University, Sevilla, Spain
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Journal Articles
- 2024
[j53]A. Gil-Gamboa
, Pilar Paneque, Oscar Trull, Alicia Troncoso:
Medium-term water consumption forecasting based on deep neural networks. Expert Syst. Appl. 247: 123234 (2024)- [j52]Rubén Pérez-Chacón, Gualberto Asencio-Cortés, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption. Future Gener. Comput. Syst. 154: 397-412 (2024) - 2023
- [j51]A. R. Troncoso-García, Isabel Brito, Alicia Troncoso, Francisco Martínez-Álvarez:
Explainable hybrid deep learning and Coronavirus Optimization Algorithm for improving evapotranspiration forecasting. Comput. Electron. Agric. 215: 108387 (2023) - [j50]Laura Melgar-García, Francisco Martínez-Álvarez, Dieu Tien Bui, Alicia Troncoso:
A novel semantic segmentation approach based on U-Net, WU-Net, and U-Net++ deep learning for predicting areas sensitive to pluvial flood at tropical area. Int. J. Digit. Earth 16(1): 3661-3679 (2023) - [j49]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso:
Identifying novelties and anomalies for incremental learning in streaming time series forecasting. Eng. Appl. Artif. Intell. 123(Part B): 106326 (2023) - [j48]P. Jiménez-Herrera, Laura Melgar-García, Gualberto Asencio-Cortés, Alicia Troncoso Lora:
Streaming big time series forecasting based on nearest similar patterns with application to energy consumption. Log. J. IGPL 31(2): 255-270 (2023) - [j47]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) - [j46]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso:
A novel distributed forecasting method based on information fusion and incremental learning for streaming time series. Inf. Fusion 95: 163-173 (2023) - [j45]Andrés Manuel Chacón-Maldonado, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Alicia Troncoso:
FS-Studio: An extensive and efficient feature selection experimentation tool for Weka Explorer. SoftwareX 23: 101401 (2023) - [j44]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) - 2022
- [j43]R. Mortazavi, S. Mortazavi, Alicia Troncoso:
Wrapper-based feature selection using regression trees to predict intrinsic viscosity of polymer. Eng. Comput. 38(3): 2553-2565 (2022) - [j42]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) - [j41]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) - [j40]Miguel Ángel Castán-Lascorz, P. Jiménez-Herrera, Alicia Troncoso Lora, Gualberto Asencio-Cortés:
A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting. Inf. Sci. 586: 611-627 (2022) - [j39]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) - 2021
- [j38]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) - [j37]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso:
Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach. Inf. Sci. 558: 174-193 (2021) - [j36]David Guijo-Rubio, Antonio Manuel Durán-Rosal, Pedro Antonio Gutiérrez, Alicia Troncoso, César Hervás-Martínez:
Time-Series Clustering Based on the Characterization of Segment Typologies. IEEE Trans. Cybern. 51(11): 5409-5422 (2021) - 2020
- [j35]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) - [j34]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) - [j33]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) - 2019
- [j32]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) - [j31]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) - [j30]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) - [j29]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) - [j28]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) - 2018
- [j27]Juan A. Nepomuceno, Alicia Troncoso, Isabel A. Nepomuceno-Chamorro, Jesús S. Aguilar-Ruiz:
Pairwise gene GO-based measures for biclustering of high-dimensional expression data. BioData Min. 11(1): 4:1-4:19 (2018) - [j26]Alicia Troncoso Lora, P. Ribera, Gualberto Asencio-Cortés, Inmaculada Vega, D. Gallego:
Imbalanced classification techniques for monsoon forecasting based on a new climatic time series. Environ. Model. Softw. 106: 48-56 (2018) - [j25]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) - [j24]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) - [j23]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) - 2017
- [j22]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) - [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]Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso, Antonio Bahamonde:
Content-based methods in peer assessment of open-response questions to grade students as authors and as graders. Knowl. Based Syst. 117: 79-87 (2017) - [j19]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) - 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, 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) - 2015
- [j15]Juan A. Nepomuceno, Alicia Troncoso, Jesús S. Aguilar-Ruiz:
Scatter search-based identification of local patterns with positive and negative correlations in gene expression data. Appl. Soft Comput. 35: 637-651 (2015) - [j14]Juan A. Nepomuceno, Alicia Troncoso Lora, Isabel A. Nepomuceno-Chamorro, Jesús S. Aguilar-Ruiz:
Integrating biological knowledge based on functional annotations for biclustering of gene expression data. Comput. Methods Programs Biomed. 119(3): 163-180 (2015) - [j13]María Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso Lora, José C. Riquelme:
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets. Integr. Comput. Aided Eng. 22(1): 21-39 (2015) - [j12]Alicia Troncoso Lora, Marta Arias, José C. Riquelme:
A multi-scale smoothing kernel for measuring time-series similarity. Neurocomputing 167: 8-17 (2015) - [j11]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) - [j10]Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso Lora, Antonio Bahamonde:
A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments. Knowl. Based Syst. 85: 322-328 (2015) - 2014
- [j9]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) - 2011
- [j8]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
Biclustering of Gene Expression Data by Correlation-Based Scatter Search. BioData Min. 4: 3 (2011) - [j7]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz:
Discovery of motifs to forecast outlier occurrence in time series. Pattern Recognit. Lett. 32(12): 1652-1665 (2011) - [j6]María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
An evolutionary algorithm to discover quantitative association rules in multidimensional time series. Soft Comput. 15(10): 2065-2084 (2011) - [j5]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz:
Energy Time Series Forecasting Based on Pattern Sequence Similarity. IEEE Trans. Knowl. Data Eng. 23(8): 1230-1243 (2011) - 2010
- [j4]A. Morales-Esteban, Francisco Martínez-Álvarez, Alicia Troncoso Lora, J. L. Justo, Cristina Rubio-Escudero:
Pattern recognition to forecast seismic time series. Expert Syst. Appl. 37(12): 8333-8342 (2010) - [j3]María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme:
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution. Integr. Comput. Aided Eng. 17(3): 227-242 (2010) - 2008
- [j2]Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jesús S. Aguilar-Ruiz, Jesús Manuel Riquelme-Santos:
Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production. Eur. J. Oper. Res. 185(3): 1114-1127 (2008) - 2006
- [j1]Alicia Troncoso Lora:
Advances in optimization and prediction techniques: Real-world applications. AI Commun. 19(3): 295-297 (2006)
Conference and Workshop Papers
- 2024
- [c64]Angela del Robledo Troncoso-García, Manuel Jesús Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso:
Ground-Level Ozone Forecasting Using Explainable Machine Learning. CAEPIA 2024: 71-80 - [c63]Francesc Rodríguez-Díaz, José Francisco Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines. CAEPIA 2024: 121-130 - 2023
- [c62]Laura Melgar-García, Angela Troncoso-García, David Gutiérrez-Avilés, José Francisco Torres, Alicia Troncoso:
Explainable Artificial Intelligence for Education: A Real Case of a University Subject Switched to Python. CISIS-ICEUTE 2023: 358-367 - [c61]Laura Melgar-García, Maryam Hosseini, Alicia Troncoso:
Identification of Anomalies in Urban Sound Data with Autoencoders. HAIS 2023: 27-38 - [c60]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 - [c59]A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora:
Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals. IWANN (1) 2023: 626-637 - [c58]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 - [c57]Andrés Manuel Chacón-Maldonado, A. R. Troncoso-García, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, Alicia Troncoso:
Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning. SOCO (2) 2023: 121-131 - [c56]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 - 2022
- [c55]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 - [c54]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso:
Nearest neighbors with incremental learning for real-time forecasting of electricity demand. ICDM (Workshops) 2022: 1-8 - [c53]A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso:
Explainable machine learning for sleep apnea prediction. KES 2022: 2930-2939 - [c52]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 - [c51]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 - [c50]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 - 2021
- [c49]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso Lora:
Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming. CAEPIA 2021: 185-195 - [c48]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 - [c47]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 - [c46]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 - 2020
- [c45]P. Jiménez-Herrera, Laura Melgar-García, Gualberto Asencio-Cortés, Alicia Troncoso:
A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series. HAIS 2020: 522-533 - [c44]Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso:
Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning. ICANN (1) 2020: 271-283 - [c43]Laura Melgar-García, David Gutiérrez-Avilés, Cristina Rubio-Escudero, Alicia Troncoso:
High-content screening images streaming analysis using the STriGen methodology. SAC 2020: 537-539 - [c42]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 - 2019
- [c41]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 - [c40]Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso:
Pattern Sequence Neural Network for Solar Power Forecasting. ICONIP (5) 2019: 727-737 - [c39]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 - [c38]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
- [c37]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 - [c36]Zheng Wang, Irena Koprinska, Alicia Troncoso, Francisco Martínez-Álvarez:
Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting. IJCNN 2018: 1-8 - [c35]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 - [c34]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
- [c33]Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso:
Scalable Forecasting Techniques Applied to Big Electricity Time Series. IWANN (2) 2017: 165-175 - [c32]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
- [c31]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 - [c30]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 - [c29]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 - [c28]Juan A. Nepomuceno, Alicia Troncoso, Isabel A. Nepomuceno-Chamorro, Jesús S. Aguilar-Ruiz:
Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure. HAIS 2016: 685-693 - [c27]Mashud Rana, Irena Koprinska, Alicia Troncoso, Vassilios G. Agelidis:
Extended Weighted Nearest Neighbor for Electricity Load Forecasting. ICANN (2) 2016: 299-307 - 2015
- [c26]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 - [c25]Oscar Luaces, Jorge Díez, Amparo Alonso-Betanzos, Alicia Troncoso, Antonio Bahamonde:
Including Content-Based Methods in Peer-Assessment of Open-Response Questions. ICDM Workshops 2015: 273-279 - [c24]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
- [c23]Mashud Rana, Irena Koprinska, Alicia Troncoso Lora:
Forecasting hourly electricity load profile using neural networks. IJCNN 2014: 824-831 - 2013
- [c22]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 - [c21]Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Combining pattern sequence similarity with neural networks for forecasting electricity demand time series. IJCNN 2013: 1-8 - [c20]Jorge García-Gutiérrez, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study. SOCO-CISIS-ICEUTE 2013: 249-258 - 2012
- [c19]Marta Arias, Alicia Troncoso Lora, José C. Riquelme:
A Kernel for Time Series Classification: Application to Atmospheric Pollutants. SOCO 2012: 417-426 - 2011
- [c18]Francisco Martínez-Álvarez, Alicia Troncoso Lora, A. Morales-Esteban, José C. Riquelme:
Computational Intelligence Techniques for Predicting Earthquakes. HAIS (2) 2011: 287-294 - [c17]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
Inferring gene coexpression networks with Biclustering based on Scatter Search. ISDA 2011: 1091-1096 - [c16]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
A local search in Scatter Search for improving Biclusters. NaBIC 2011: 521-526 - 2010
- [c15]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
Correlation-Based Scatter Search for Discovering Biclusters from Gene Expression Data. EvoBIO 2010: 122-133 - [c14]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
Evolutionary metaheuristic for biclustering based on linear correlations among genes. SAC 2010: 1143-1147 - 2009
- [c13]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences. IDA 2009: 357-368 - [c12]María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme:
Quantitative Association Rules Applied to Climatological Time Series Forecasting. IDEAL 2009: 284-291 - [c11]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
An Overlapping Control-Biclustering Algorithm from Gene Expression Data. ISDA 2009: 1239-1244 - [c10]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz:
A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms. PRIB 2009: 199-210 - 2008
- [c9]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz:
LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series. ICDM 2008: 453-461 - 2007
- [c8]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jesús S. Aguilar-Ruiz:
Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines. CBMS 2007: 141-146 - [c7]Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, Jorge García-Gutiérrez:
Biclusters Evaluation Based on Shifting and Scaling Patterns. IDEAL 2007: 840-849 - [c6]Francisco Martínez-Álvarez, Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jesús Manuel Riquelme-Santos:
Partitioning-Clustering Techniques Applied to the Electricity Price Time Series. IDEAL 2007: 990-999 - 2003
- [c5]Alicia Troncoso Lora, Jesús Manuel Riquelme-Santos, José Cristóbal Riquelme Santos, Antonio Gómez Expósito, José Luís Martínez Ramos:
Time-Series Prediction: Application to the Short-Term Electric Energy Demand. CAEPIA 2003: 577-586 - [c4]Alicia Troncoso Lora, José Cristóbal Riquelme Santos, José Luís Martínez Ramos, Jesús Manuel Riquelme-Santos, Antonio Gómez Expósito:
Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production. CAEPIA 2003: 656-665 - [c3]Alicia Troncoso Lora, José Cristóbal Riquelme Santos, José Luís Martínez Ramos, Jesús Manuel Riquelme-Santos, Antonio Gómez Expósito:
Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production. EPIA 2003: 189-203 - 2002
- [c2]Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jesús Manuel Riquelme-Santos, José Luís Martínez Ramos, Antonio Gómez Expósito:
Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours. DEXA 2002: 321-330 - [c1]Alicia Troncoso Lora, Jesús Manuel Riquelme-Santos, José Cristóbal Riquelme Santos, Antonio Gómez Expósito, José Luís Martínez Ramos:
A Comparison of Two Techniques for Next-Day Electricity Price Forecasting. IDEAL 2002: 384-390
Editorship
- 2025
- [e18]Héctor Quintián, Emilio Corchado, Alicia Troncoso Lora, Hilde Pérez García, Esteban Jove-Pérez, José Luís Calvo-Rolle, Francisco Javier Martínez de Pisón, Pablo García Bringas, Francisco Martínez-Álvarez, Álvaro Herrero, Paolo Fosci:
Hybrid Artificial Intelligent Systems - 19th International Conference, HAIS 2024, Salamanca, Spain, October 9-11, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14857, Springer 2025, ISBN 978-3-031-74182-1 [contents] - [e17]Héctor Quintián, Emilio Corchado, Alicia Troncoso Lora, Hilde Pérez García, Esteban Jove-Pérez, José Luís Calvo-Rolle, Francisco Javier Martínez de Pisón, Pablo García Bringas, Francisco Martínez-Álvarez, Álvaro Herrero, Paolo Fosci:
Hybrid Artificial Intelligent Systems - 19th International Conference, HAIS 2024, Salamanca, Spain, October 9-11, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14858, Springer 2025, ISBN 978-3-031-74185-2 [contents] - 2024
- [e16]Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Verónica Bolón-Canedo, Elena Hernández-Pereira, Oscar Fontenla-Romero, David Camacho, Juan Ramón Rabuñal, Manuel Ojeda-Aciego, Jesús Medina, José C. Riquelme, Alicia Troncoso:
Advances in Artificial Intelligence - 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19-21, 2024, Proceedings. Lecture Notes in Computer Science 14640, Springer 2024, ISBN 978-3-031-62798-9 [contents] - 2023
- [e15]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] - [e14]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] - [e13]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] - [e12]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] - [e11]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] - [e10]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
- [e9]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
- [e8]Enrique Alba, Gabriel Luque, Francisco Chicano, Carlos Cotta, David Camacho, Manuel Ojeda-Aciego, Susana Montes, Alicia Troncoso, José C. Riquelme, Rodrigo Gil-Merino:
Advances in Artificial Intelligence - 19th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2020/2021, Málaga, Spain, September 22-24, 2021, Proceedings. Lecture Notes in Computer Science 12882, Springer 2021, ISBN 978-3-030-85712-7 [contents] - 2020
- [e7]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] - [e6]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] - 2018
- [e5]Francisco Herrera, Sergio Damas, Rosana Montes, Sergio Alonso, Oscar Cordón, Antonio González, Alicia Troncoso:
Advances in Artificial Intelligence - 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, Granada, Spain, October 23-26, 2018, Proceedings. Lecture Notes in Computer Science 11160, Springer 2018, ISBN 978-3-030-00373-9 [contents] - 2016
- [e4]Oscar Luaces, José A. Gámez, Edurne Barrenechea, Alicia Troncoso, Mikel Galar, Héctor Quintián, Emilio Corchado:
Advances in Artificial Intelligence - 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, Salamanca, Spain, September 14-16, 2016. Proceedings. Lecture Notes in Computer Science 9868, Springer 2016, ISBN 978-3-319-44635-6 [contents] - [e3]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
- [e2]José Miguel Puerta, José A. Gámez, Bernabé Dorronsoro, Edurne Barrenechea, Alicia Troncoso, Bruno Baruque, Mikel Galar:
Advances in Artificial Intelligence - 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015, Albacete, Spain, November 9-12, 2015, Proceedings. Lecture Notes in Computer Science 9422, Springer 2015, ISBN 978-3-319-24597-3 [contents] - 2013
- [e1]Concha Bielza, Antonio Salmerón, Amparo Alonso-Betanzos, José Ignacio Hidalgo, Luis Martínez-López, Alicia Troncoso Lora, Emilio Corchado, Juan M. Corchado:
Advances in Artificial Intelligence - 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. Proceedings. Lecture Notes in Computer Science 8109, Springer 2013, ISBN 978-3-642-40642-3 [contents]
Informal and Other Publications
- 2020
- [i2]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) - 2018
- [i1]David Guijo-Rubio, Antonio Manuel Durán-Rosal, Pedro Antonio Gutiérrez, Alicia Troncoso, César Hervás-Martínez:
Time series clustering based on the characterisation of segment typologies. CoRR abs/1810.11624 (2018)
Coauthor Index
Francisco J. Martínez de Pisón Ascacibar
aka: Francisco Javier Martínez de Pisón
aka: Francisco Javier Martínez de Pisón
Emilio Corchado
aka: Emilio S. Corchado Rodríguez
aka: Emilio S. Corchado Rodríguez
[j52] [j51] [j50] [j47] [j45] [j44] [j42] [j41] [j39] [j38] [j35] [j34] [j33] [j32] [j31] [j30] [j29] [j28] [j25] [j24] [j23] [j22] [j21] [j19] [j18] [j17] [j16] [j11] [j9] [j7] [j6] [j5] [j4] [j3] [c64] [c63] [c60] [c59] [c58] [c57] [c56] [c55] [c53] [c52] [c51] [c50] [c48] [c47] [c46] [c42] [c41] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c26] [c24] [c22] [c21] [c20] [c18] [c13] [c12] [c9] [c8] [c6] [e18] [e17] [e15] [e14] [e13] [e12] [e11] [e10] [e9] [e7] [e6] [e3] [i2]
José Cristóbal Riquelme Santos
aka: José C. Riquelme
aka: José C. Riquelme
José F. Torres
aka: José Francisco Torres
aka: José Francisco Torres
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