José C. Riquelme

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 44

Top Topics

Quantitative Association Rules

Drift Detection

Feature Selection

Top Venues

Publications

Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, Isabel Sofia Brito, José C. Riquelme, María Martínez-Ballesteros
Evolutionary Feature Selection for Time-Series Forecasting. SAC (2024)
Miguel Campos-Romero, Manuel Carranza-García, José C. Riquelme
Advancing unsupervised anomaly detection with normalizing flow and multi-scale ensemble learning. Eng. Appl. Artif. Intell. 137 (2024)
Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, José C. Riquelme, María Martínez-Ballesteros
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting. CAEPIA (2024)
Pablo Reina-Jiménez, Manuel Carranza-García, José María Luna-Romera, José C. Riquelme
Efficient Short-Term Time Series Forecasting with Regression Trees. SOCO (2) (2023)
Pedro Lara-Benítez, Manuel Carranza-García, David Gutiérrez-Avilés, José C. Riquelme
Data streams classification using deep learning under different speeds and drifts. Log. J. IGPL 31 (4) (2023)
Belén Vega-Márquez, Juan Pardo-Martínez, María del Mar Villegas-Oliva, José C. Riquelme
Forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia. SOCO (1) (2023)
Pedro Lara-Benítez, Manuel Carranza-García, José María Luna-Romera, José C. Riquelme
Short-term solar irradiance forecasting in streaming with deep learning. Neurocomputing 546 (2023)
José David Martín-Fernández, Beatriz Pontes, José C. Riquelme
Simultaneous Evolutionary Optimization of Features Subset and Clusters Number. GECCO Companion (2023)
M. Lourdes Linares-Barrera, María Martínez-Ballesteros, José Manuel García-Heredia, José C. Riquelme
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma. HAIS (2023)
Manuel Carranza-García, José C. Riquelme, Avideh Zakhor
Temporal Axial Attention For Lidar-Based 3d Object Detection In Autonomous Driving. ICIP (2022)
Manuel Carranza-García, F. Javier Galán-Sales, José María Luna-Romera, José C. Riquelme
Object detection using depth completion and camera-LiDAR fusion for autonomous driving. Integr. Comput. Aided Eng. 29 (3) (2022)
Tomás Cabello-López, Manuel Cañizares-Juan, Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation. HAIS (2022)
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
An Experimental Review on Deep Learning Architectures for Time Series Forecasting. Int. J. Neural Syst. 31 (3) (2021)
Belén Vega-Márquez, Isabel A. Nepomuceno-Chamorro, Cristina Rubio-Escudero, José C. Riquelme
OCEAn: Ordinal classification with an ensemble approach. Inf. Sci. 580 (2021)
Manuel Carranza-García, Pedro Lara-Benítez, José María Luna-Romera, José C. Riquelme
Feature Selection on Spatio-Temporal Data for Solar Irradiance Forecasting. SOCO (2021)
Manuel Carranza-García, Pedro Lara-Benítez, Jorge García-Gutiérrez, José C. Riquelme
Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance. Neurocomputing 449 (2021)
Manuel Carranza-García, Pedro Lara-Benítez, Jorge García-Gutiérrez, José C. Riquelme
Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class Imbalance. CoRR (2021)
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
An Experimental Review on Deep Learning Architectures for Time Series Forecasting. CoRR (2021)
Pedro Lara-Benítez, Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
Asynchronous dual-pipeline deep learning framework for online data stream classification. Integr. Comput. Aided Eng. 27 (2) (2020)
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)
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) (2020)
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)
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 (2020)
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 (2020)
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz
Filter-based feature selection in the context of evolutionary neural networks in supervised machine learning. Pattern Anal. Appl. 23 (1) (2020)
José María Luna-Romera, María Martínez-Ballesteros, Jorge García-Gutiérrez, José C. Riquelme
External clustering validity index based on chi-squared statistical test. Inf. Sci. 487 (2019)
Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks. Remote. Sens. 11 (3) (2019)
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz
Semi-wrapper feature subset selector for feed-forward neural networks: Applications to binary and multi-class classification problems. Neurocomputing 353 (2019)
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 (2019)
José María Luna-Romera, Fernando Núñez-Hernández, María Martínez-Ballesteros, José C. Riquelme, Carlos Usabiaga
Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning. IEEE Access 7 (2019)
Belén Vega-Márquez, Cristina Rubio-Escudero, José C. Riquelme, Isabel A. Nepomuceno-Chamorro
Creation of Synthetic Data with Conditional Generative Adversarial Networks. SOCO (2019)
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)
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)
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 (2018)
Antonio J. Tallón-Ballesteros, José C. Riquelme
Low Dimensionality or Same Subsets as a Result of Feature Selection: An In-Depth Roadmap. IWINAC (2) (2017)
Francisco Martínez-Álvarez, Alicia Troncoso, Jorge Reyes, María Martínez-Ballesteros, José C. Riquelme
Applications of Computational Intelligence in Time Series. Comput. Intell. Neurosci. 2017 (2017)
Amparo Alonso-Betanzos, José A. Gámez, Francisco Herrera, José Miguel Puerta, José C. Riquelme
Volume, variety and velocity in Data Science. Knowl. Based Syst. 117 (2017)
María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez, José C. Riquelme
Obtaining optimal quality measures for quantitative association rules. Neurocomputing 176 (2016)
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) (2016)
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz Sánchez
Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection. HAIS (2016)
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) (2015)
Alicia Troncoso Lora, Marta Arias, José C. Riquelme
A multi-scale smoothing kernel for measuring time-series similarity. Neurocomputing 167 (2015)
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 (2015)
Antonio J. Tallón-Ballesteros, José C. Riquelme
Data Cleansing Meets Feature Selection: A Supervised Machine Learning Approach. IWINAC (2) (2015)
Antonio J. Tallón-Ballesteros, José C. Riquelme
Tackling Ant Colony Optimization Meta-Heuristic as Search Method in Feature Subset Selection Based on Correlation or Consistency Measures. IDEAL (2014)
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
Selecting the best measures to discover quantitative association rules. Neurocomputing 126 (2014)
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
Discovering gene association networks by multi-objective evolutionary quantitative association rules. J. Comput. Syst. Sci. 80 (1) (2014)
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 (2014)
Daniel Rodríguez, Israel Herraiz, Rachel Harrison, José Javier Dolado, José C. Riquelme
Preliminary comparison of techniques for dealing with imbalance in software defect prediction. EASE (2014)
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)
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Rachel Harrison
A study of subgroup discovery approaches for defect prediction. Inf. Softw. Technol. 55 (10) (2013)
Antonio J. Tallón-Ballesteros, César Hervás-Martínez, José C. Riquelme, Roberto Ruiz
Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems. Neurocomputing 114 (2013)
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)
Francisco Fernández-Navarro, César Hervás-Martínez, Roberto Ruiz, José C. Riquelme
Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection. Appl. Soft Comput. 12 (6) (2012)
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz
Searching for rules to detect defective modules: A subgroup discovery approach. Inf. Sci. 191 (2012)
Marta Arias, Alicia Troncoso Lora, José C. Riquelme
A Kernel for Time Series Classification: Application to Atmospheric Pollutants. SOCO (2012)
Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz, Miguel García-Torres
Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches. Expert Syst. Appl. 39 (12) (2012)
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
Revisiting the yeast cell cycle problem with the improved TriGen algorithm. NaBIC (2011)
Daniel Rodríguez, Mercedes Ruiz Carreira, José C. Riquelme, Rachel Harrison
Multiobjective simulation optimisation in software project management. GECCO (2011)
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) (2011)
Antonio J. Tallón-Ballesteros, César Hervás-Martínez, José C. Riquelme, Roberto Ruiz
Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection. IWINAC (2) (2011)
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) (2011)
Cristina Rubio-Escudero, Francisco Martínez-Álvarez, María Martínez-Ballesteros, José C. Riquelme
On the use of algorithms to discover motifs in DNA sequences. ISDA (2011)
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
Triclustering on temporary microarray data using the TriGen algorithm. ISDA (2011)
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Rachel Harrison
Subgroup Discovery for Defect Prediction. SSBSE (2011)
Francisco Martínez-Álvarez, Alicia Troncoso Lora, A. Morales-Esteban, José C. Riquelme
Computational Intelligence Techniques for Predicting Earthquakes. HAIS (2) (2011)
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) (2011)
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
Unravelling the Yeast Cell Cycle Using the TriGen Algorithm. CAEPIA (2011)
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
Inferring gene-gene associations from Quantitative Association Rules. ISDA (2011)
María Martínez-Ballesteros, Cristina Rubio-Escudero, José C. Riquelme, Francisco Martínez-Álvarez
Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms. ICAART (1) (2011)
Isabel A. Nepomuceno-Chamorro, Jesús S. Aguilar-Ruiz, José C. Riquelme
Inferring gene regression networks with model trees. BMC Bioinform. 11 (2010)
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) (2010)
Francisco Fernández-Navarro, César Hervás-Martínez, Pedro Antonio Gutiérrez, Roberto Ruiz, José C. Riquelme
-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection. ICANN (1) (2010)
Jorge García-Gutiérrez, Francisco Martínez-Álvarez, José C. Riquelme
Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps. IEA/AIE (1) (2010)
Daniel Rodríguez, José Javier Dolado, José C. Riquelme, Roberto Ruiz, Miguel-Ángel Sicilia
Knowledge representation and applied decision making (KREAM). ICCS (1) (2010)
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
Quantitative Association Rules Applied to Climatological Time Series Forecasting. IDEAL (2009)
Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences. IDA (2009)
Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz
Best Agglomerative Ranked Subset for Feature Selection. FSDM (2008)
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)
José C. Riquelme, Roberto Ruiz, Daniel Rodríguez
Identificación de Fallos en Módulos Software. JISBD (2008)
Francisco J. Ferrer-Troyano, Jesús S. Aguilar-Ruiz, José C. Riquelme
FACIL - An approach for classifying data streams by decision rules and border examples. Monde des Util. Anal. Données 36 (2007)
José C. Riquelme, Roberto Ruiz, Karina Gilbert
Data Mining: Concepts and Trends. Inteligencia Artif. 10 (29) (2006)
Roberto Ruiz, Karina Gilbert, José C. Riquelme
Special Issue: Data Mining. Inteligencia Artif. 10 (29) (2006)
Miguel A. Ridao, Eduardo F. Camacho, José C. Riquelme, Miguel Toro
An evolutionary and local search algorithm for motion planning of two manipulators. J. Field Robotics 18 (8) (2001)
José C. Riquelme, Miguel A. Ridao, Eduardo F. Camacho, Miguel Toro
Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion. ICANNGA (1997)