José C. Riquelme

91 papers A* 1A 2B 3C 5Misc 7Journal 46Unranked 24
YearRankTypeTitle / Venue / Authors
2026 J jnl
MuDeNet: A multi-patch descriptor network for anomaly modeling.
Inf. Fusion
Miguel Campos-Romero, Manuel Carranza-García, Robert-Jan Sips, José C. Riquelme
2026 J jnl
Tree-based vs. deep learning in time series: A prescriptive framework for performance-driven model selection.
Appl. Soft Comput.
Pablo Reina-Jiménez, María Martínez-Ballesteros, José C. Riquelme
2025 — conf
Deep Learning or Trees? A Trade-off Analysis for Multivariate Time Series Forecasting.
IWANN (1)
Pablo Reina-Jiménez, María Martínez-Ballesteros, José C. Riquelme
2024 — ed.
Advances in Artificial Intelligence - 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19-21, 2024, Proceedings
CAEPIA
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
2024 J jnl
Advancing unsupervised anomaly detection with normalizing flow and multi-scale ensemble learning.
Eng. Appl. Artif. Intell.
Miguel Campos-Romero, Manuel Carranza-García, José C. Riquelme
2024 Misc conf
Evolutionary Feature Selection for Time-Series Forecasting.
SAC
Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, Isabel Sofia Brito, José C. Riquelme, María Martínez-Ballesteros
2024 — conf
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting.
CAEPIA
Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, José C. Riquelme, María Martínez-Ballesteros
2023 Misc conf
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma.
HAIS
Maria Lourdes Linares-Barrera, María Martínez-Ballesteros, José Manuel García-Heredia, José C. Riquelme
2023 J jnl
Data streams classification using deep learning under different speeds and drifts.
Log. J. IGPL
Pedro Lara-Benítez, Manuel Carranza-García, David Gutiérrez-Avilés, José C. Riquelme
2023 — conf
Efficient Short-Term Time Series Forecasting with Regression Trees.
SOCO (2)
Pablo Reina-Jiménez, Manuel Carranza-García, José María Luna-Romera, José C. Riquelme
2023 — conf
Forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia.
SOCO (1)
Belén Vega-Márquez, Juan Pardo-Martínez, María del Mar Villegas-Oliva, José C. Riquelme
2023 J jnl
Short-term solar irradiance forecasting in streaming with deep learning.
Neurocomputing
Pedro Lara-Benítez, Manuel Carranza-García, José María Luna-Romera, José C. Riquelme
2023 — conf
Simultaneous Evolutionary Optimization of Features Subset and Clusters Number.
GECCO Companion
José David Martín-Fernández, Beatriz Pontes, José C. Riquelme
2022 Misc conf
Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation.
HAIS
Tomás Cabello-López, Manuel Cañizares-Juan, Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
2022 J jnl
Object detection using depth completion and camera-LiDAR fusion for autonomous driving.
Integr. Comput. Aided Eng.
Manuel Carranza-García, Francisco Javier Galán-Sales, José María Luna-Romera, José C. Riquelme
2022 B conf
Temporal Axial Attention For Lidar-Based 3d Object Detection In Autonomous Driving.
ICIP
Manuel Carranza-García, José C. Riquelme, Avideh Zakhor
2021 — ed.
Advances in Artificial Intelligence - 19th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2020/2021, Málaga, Spain, September 22-24, 2021, Proceedings
CAEPIA
Enrique Alba, Gabriel Luque, Francisco Chicano, Carlos Cotta, David Camacho, Manuel Ojeda-Aciego, Susana Montes, Alicia Troncoso, José C. Riquelme, Rodrigo Gil-Merino
2021 J jnl
An Experimental Review on Deep Learning Architectures for Time Series Forecasting.
CoRR
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
2021 J jnl
An Experimental Review on Deep Learning Architectures for Time Series Forecasting.
Int. J. Neural Syst.
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
2021 J jnl
Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class Imbalance.
CoRR
Manuel Carranza-García, Pedro Lara-Benítez, Jorge García-Gutiérrez, José C. Riquelme
2021 J jnl
Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance.
Neurocomputing
Manuel Carranza-García, Pedro Lara-Benítez, Jorge García-Gutiérrez, José C. Riquelme
2021 — conf
Feature Selection on Spatio-Temporal Data for Solar Irradiance Forecasting.
SOCO
Manuel Carranza-García, Pedro Lara-Benítez, José María Luna-Romera, José C. Riquelme
2021 J jnl
OCEAn: Ordinal classification with an ensemble approach.
Inf. Sci.
Belén Vega-Márquez, Isabel A. Nepomuceno-Chamorro, Cristina Rubio-Escudero, José C. Riquelme
2020 — conf
A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets.
SOCO
Miguel Ángel Molina, Gualberto Asencio-Cortés, José C. Riquelme, Francisco Martínez-Álvarez
2020 J jnl
Asynchronous dual-pipeline deep learning framework for online data stream classification.
Integr. Comput. Aided Eng.
Pedro Lara-Benítez, Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
2020 J jnl
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model.
Big Data
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
2020 J jnl
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model.
CoRR
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
2020 J jnl
Filter-based feature selection in the context of evolutionary neural networks in supervised machine learning.
Pattern Anal. Appl.
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz
2020 — conf
On the Performance of Deep Learning Models for Time Series Classification in Streaming.
SOCO
Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme
2020 J jnl
On the performance of deep learning models for time series classification in streaming.
CoRR
Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme
2019 J jnl
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks.
Remote. Sens.
Manuel Carranza-García, Jorge García-Gutiérrez, José C. Riquelme
2019 J jnl
A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System.
IEEE Access
Catalina Gomez-Quiles, Gualberto Asencio-Cortés, Adolfo Gastalver-Rubio, Francisco Martínez-Álvarez, Alicia Troncoso, Joan Manresa, José C. Riquelme, Jesús Manuel Riquelme-Santos
2019 J jnl
Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning.
IEEE Access
José María Luna-Romera, Fernando Núñez-Hernández, María Martínez-Ballesteros, José C. Riquelme, Carlos Usabiaga
2019 — conf
Creation of Synthetic Data with Conditional Generative Adversarial Networks.
SOCO
Belén Vega-Márquez, Cristina Rubio-Escudero, José C. Riquelme, Isabel A. Nepomuceno-Chamorro
2019 J jnl
External clustering validity index based on chi-squared statistical test.
Inf. Sci.
José María Luna-Romera, María Martínez-Ballesteros, Jorge García-Gutiérrez, José C. Riquelme
2019 J jnl
Semi-wrapper feature subset selector for feed-forward neural networks: Applications to binary and multi-class classification problems.
Neurocomputing
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz
2018 J jnl
A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information.
Environ. Model. Softw.
Álvaro Gómez-Losada, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, José C. Riquelme
2018 — conf
Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses.
SOCO-CISIS-ICEUTE
Cristina Rubio-Escudero, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme
2018 Misc conf
SmartFD: A Real Big Data Application for Electrical Fraud Detection.
HAIS
David Gutiérrez-Avilés, J. A. Fábregas, J. Tejedor, Francisco Martínez-Álvarez, Alicia Troncoso, A. Arcos, José C. Riquelme
2017 J jnl
Applications of Computational Intelligence in Time Series.
Comput. Intell. Neurosci.
Francisco Martínez-Álvarez, Alicia Troncoso, Jorge Reyes, María Martínez-Ballesteros, José C. Riquelme
2017 — conf
Low Dimensionality or Same Subsets as a Result of Feature Selection: An In-Depth Roadmap.
IWINAC (2)
Antonio J. Tallón-Ballesteros, José C. Riquelme
2017 J jnl
Volume, variety and velocity in Data Science.
Knowl. Based Syst.
Amparo Alonso-Betanzos, José A. Gámez, Francisco Herrera, José M. Puerta, José C. Riquelme
2016 Misc conf
Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection.
HAIS
Antonio J. Tallón-Ballesteros, José C. Riquelme, Roberto Ruiz Sánchez
2016 J jnl
Improving a multi-objective evolutionary algorithm to discover quantitative association rules.
Knowl. Inf. Syst.
María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme
2016 J jnl
Obtaining optimal quality measures for quantitative association rules.
Neurocomputing
María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez, José C. Riquelme
2015 J jnl
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables.
Neurocomputing
Jorge García-Gutiérrez, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2015 J jnl
A multi-scale smoothing kernel for measuring time-series similarity.
Neurocomputing
Alicia Troncoso Lora, Marta Arias, José C. Riquelme
2015 — conf
Data Cleansing Meets Feature Selection: A Supervised Machine Learning Approach.
IWINAC (2)
Antonio J. Tallón-Ballesteros, José C. Riquelme
2015 J jnl
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integr. Comput. Aided Eng.
María Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso Lora, José C. Riquelme
2014 — ch.
Data Mining Methods Applied to a Digital Forensics Task for Supervised Machine Learning.
Computational Intelligence in Digital Forensics
Antonio J. Tallón-Ballesteros, José C. Riquelme
2014 J jnl
Discovering gene association networks by multi-objective evolutionary quantitative association rules.
J. Comput. Syst. Sci.
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
2014 A conf
Preliminary comparison of techniques for dealing with imbalance in software defect prediction.
EASE
Daniel Rodríguez, Israel Herraiz, Rachel Harrison, José Javier Dolado, José C. Riquelme
2014 J jnl
Selecting the best measures to discover quantitative association rules.
Neurocomputing
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2014 C conf
Tackling Ant Colony Optimization Meta-Heuristic as Search Method in Feature Subset Selection Based on Correlation or Consistency Measures.
IDEAL
Antonio J. Tallón-Ballesteros, José C. Riquelme
2014 J jnl
TriGen: A genetic algorithm to mine triclusters in temporal gene expression data.
Neurocomputing
David Gutiérrez-Avilés, Cristina Rubio-Escudero, Francisco Martínez-Álvarez, José C. Riquelme
2013 — conf
A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study.
SOCO-CISIS-ICEUTE
Jorge García-Gutiérrez, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2013 J jnl
A study of subgroup discovery approaches for defect prediction.
Inf. Softw. Technol.
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Rachel Harrison
2013 J jnl
Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems.
Neurocomputing
Antonio J. Tallón-Ballesteros, César Hervás-Martínez, José C. Riquelme, Roberto Ruiz
2013 Misc conf
ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules.
HAIS
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2012 — conf
A Kernel for Time Series Classification: Application to Atmospheric Pollutants.
SOCO
Marta Arias, Alicia Troncoso Lora, José C. Riquelme
2012 J jnl
Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection.
Appl. Soft Comput.
Francisco Fernández-Navarro, César Hervás-Martínez, Roberto Ruiz, José C. Riquelme
2012 J jnl
Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches.
Expert Syst. Appl.
Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz, Miguel García-Torres
2012 J jnl
Searching for rules to detect defective modules: A subgroup discovery approach.
Inf. Sci.
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz
2011 J jnl
An evolutionary algorithm to discover quantitative association rules in multidimensional time series.
Soft Comput.
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2011 — conf
Computational Intelligence Techniques for Predicting Earthquakes.
HAIS (2)
Francisco Martínez-Álvarez, Alicia Troncoso Lora, A. Morales-Esteban, José C. Riquelme
2011 J jnl
Discovery of motifs to forecast outlier occurrence in time series.
Pattern Recognit. Lett.
Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz
2011 J jnl
Energy Time Series Forecasting Based on Pattern Sequence Similarity.
IEEE Trans. Knowl. Data Eng.
Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz
2011 — conf
Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection.
IWINAC (2)
Antonio J. Tallón-Ballesteros, César Hervás-Martínez, José C. Riquelme, Roberto Ruiz
2011 C conf
Inferring gene-gene associations from Quantitative Association Rules.
ISDA
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
2011 — conf
Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms.
ICAART (1)
María Martínez-Ballesteros, Cristina Rubio-Escudero, José C. Riquelme, Francisco Martínez-Álvarez
2011 A conf
Multiobjective simulation optimisation in software project management.
GECCO
Daniel Rodríguez, Mercedes Ruiz-Carreira, José C. Riquelme, Rachel Harrison
2011 C conf
On the use of algorithms to discover motifs in DNA sequences.
ISDA
Cristina Rubio-Escudero, Francisco Martínez-Álvarez, María Martínez-Ballesteros, José C. Riquelme
2011 — conf
Revisiting the yeast cell cycle problem with the improved TriGen algorithm.
NaBIC
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
2011 B conf
Subgroup Discovery for Defect Prediction.
SSBSE
Daniel Rodríguez, Roberto Ruiz, José C. Riquelme, Rachel Harrison
2011 C conf
Triclustering on temporary microarray data using the TriGen algorithm.
ISDA
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
2011 — conf
Unravelling the Yeast Cell Cycle Using the TriGen Algorithm.
CAEPIA
David Gutiérrez-Avilés, Cristina Rubio-Escudero, José C. Riquelme
2010 — conf
Evolutionary
ICANN (1)
Francisco Fernández-Navarro, César Hervás-Martínez, Pedro Antonio Gutiérrez, Roberto Ruiz, José C. Riquelme
2010 J jnl
Inferring gene regression networks with model trees.
BMC Bioinform.
Isabel A. Nepomuceno-Chamorro, Jesús S. Aguilar-Ruiz, José C. Riquelme
2010 Misc conf
Knowledge representation and applied decision making (KREAM).
ICCS
Daniel Rodríguez, José Javier Dolado, José C. Riquelme, Roberto Ruiz, Miguel-Ángel Sicilia
2010 J jnl
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution.
Integr. Comput. Aided Eng.
María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme
2010 — conf
Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps.
IEA/AIE (1)
Jorge García-Gutiérrez, Francisco Martínez-Álvarez, José C. Riquelme
2009 B conf
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences.
IDA
Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2009 C conf
Quantitative Association Rules Applied to Climatological Time Series Forecasting.
IDEAL
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2008 — conf
Best Agglomerative Ranked Subset for Feature Selection.
FSDM
Roberto Ruiz, José C. Riquelme, Jesús S. Aguilar-Ruiz
2008 — conf
Identificación de Fallos en Módulos Software.
JISBD
José C. Riquelme, Roberto Ruiz, Daniel Rodríguez
2008 A* conf
LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series.
ICDM
Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme, Jesús S. Aguilar-Ruiz
2007 J jnl
FACIL - An approach for classifying data streams by decision rules and border examples.
Monde des Util. Anal. Données
Francisco J. Ferrer-Troyano, Jesús S. Aguilar-Ruiz, José C. Riquelme
2006 J jnl
Data Mining: Concepts and Trends.
Inteligencia Artif.
José C. Riquelme, Roberto Ruiz, Karina Gilbert
2006 J jnl
Special Issue: Data Mining.
Inteligencia Artif.
Roberto Ruiz, Karina Gilbert, José C. Riquelme
2001 J jnl
An evolutionary and local search algorithm for motion planning of two manipulators.
J. Field Robotics
Miguel A. Ridao, Eduardo F. Camacho, José C. Riquelme, Miguel Toro
1997 — conf
Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion.
ICANNGA
José C. Riquelme, Miguel A. Ridao, Eduardo F. Camacho, Miguel Toro