Artículo | 2025 |
Nonlinear Ensemble Deep Learning Model for Energy Consumption Prediction with Bayesian Optimization
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Communications on Applied Nonlinear Analysis |
Editorial | 2024 |
Advances in time series forecasting: innovative methods and applications
|
AIMS Mathematics |
Artículo | 2024 |
Embedded feature selection for neural networks via learnable drop layer
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Logic Journal of the IGPL |
Ponencia | 2024 |
Evolutionary Feature Selection for Time-Series Forecasting
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Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing |
Artículo | 2024 |
Explainable deep learning on multi-target time series forecasting: an air pollution use case
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Results in Engineering |
Ponencia | 2024 |
Explainable Deep Learning with Embedded Feature Selection for Electricity Demand Forecasting
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2024 International Conference on Smart Systems and Technologies (SST) |
Artículo | 2024 |
Explaining deep learning models for ozone pollution prediction via embedded feature selection
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APPLIED SOFT COMPUTING |
Artículo | 2024 |
From simple to complex: a sequential method for enhancing time series forecasting with deep learning
|
Logic Journal of the IGPL |
Capítulo | 2024 |
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting
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ADVANCES IN ARTIFICIAL INTELLIGENCE |
Capítulo | 2024 |
Time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection
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Lecture Notes in Networks and Systems |
Capítulo | 2024 |
Uso de herramientas software colaborativas para el seguimiento, estudio y evaluación de clases de enseñanzas prácticas y desarrollo
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Enseñanza e innovación educativa en el ámbito universitario |
Capítulo | 2024 |
Uso de herramientas software colaborativas para el seguimiento, estudio y evaluación de clases de enseñanzas prácticas y desarrollo
|
Enseñanza e innovación educativa en el ámbito universitario |
Artículo | 2023 |
A Bayesian optimization-based LSTM model for wind power forecasting in the Adama district, Ethiopia
|
ENERGIES |
Ponencia | 2023 |
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal
|
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing |
Ponencia | 2023 |
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma
|
Lecture Notes in Computer Science |
Artículo | 2023 |
A new approach based on association rules to add explainability to time series forecasting models
|
INFORMATION FUSION |
Artículo | 2023 |
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting
|
Journal of Big Data |
Ponencia | 2023 |
A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia
|
Lecture Notes in Computer Science |
Letter | 2023 |
A new treatment for sarcoma extracted from combination of miRNA deregulation and gene association rules.
|
Signal Transduction and Targeted Therapy |
Ponencia | 2023 |
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation
|
Lecture Notes in Networks and Systems |
Capítulo | 2023 |
Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals
|
Advances in Computational Intelligence |
Capítulo | 2023 |
Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning
|
Advances in Computational Intelligence |
Ponencia | 2023 |
Evolutionary computation to explain deep learning models for time series forecasting
|
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing |
Ponencia | 2023 |
Explaining Learned Patterns in Deep Learning by Association Rules Mining
|
Lecture Notes in Networks and Systems |
Ponencia | 2023 |
Feature-Aware Drop Layer (FADL): a nonparametric neural network layer for feature selection
|
Lecture Notes in Networks and Systems |
Artículo | 2023 |
PHILNet: A novel efficient approach for time series forecasting using deep learning
|
INFORMATION SCIENCES |
Ponencia | 2022 |
A novel approach to discover numerical association based on the coronavirus optimization algorithm
|
Proceedings of the ACM Symposium on Applied Computing |
Ponencia | 2022 |
Explainable machine learning for sleep apnea prediction
|
Procedia Computer Science |
Artículo | 2020 |
Autoencoded DNA methylation data to predict breast cancer recurrence: machine learning models and gene-weight significance
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Artificial Intelligence in Medicine |
Artículo | 2019 |
Analysis of the evolution of the Spanish labour market through unsupervised learning
|
IEEE ACCESS |
Artículo | 2019 |
External clustering validity index based on chi-squared statistical test
|
INFORMATION SCIENCES |
Artículo | 2018 |
An approach to validity indices for clustering techniques in Big Data
|
PROGRESS IN ARTIFICIAL INTELLIGENCE |
Capítulo | 2018 |
Aproximación al índice externo de validación de clustering basado en chi cuadrado
|
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018) 23-26 de octubre de 2018 Granada, España |
Artículo | 2018 |
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
|
KNOWLEDGE-BASED SYSTEMS |
Artículo | 2017 |
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
|
JOURNAL OF BIOMEDICAL INFORMATICS |
Editorial | 2017 |
Applications of Computational Intelligence in Time Series
|
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE |
Artículo | 2017 |
Machine learning techniques to discover genes with potential prognosis role in Alzheimer's disease using different biological sources
|
INFORMATION FUSION |
Ponencia | 2017 |
Predicción de módulos defectuosos como un problema de optimización multiobjetivo
|
Actas de las 22nd Jornadas de Ingeniería del Software y Bases de Datos, JISBD 2017 |
Ponencia | 2016 |
A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting
|
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS |
Ponencia | 2016 |
An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark
|
ADVANCES IN ARTIFICIAL INTELLIGENCE, CAEPIA 2016 |
Ponencia | 2016 |
Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules
|
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS |
Artículo | 2016 |
Improving a multi-objective evolutionary algorithm to discover quantitative association rules
|
KNOWLEDGE AND INFORMATION SYSTEMS |
Artículo | 2016 |
Obtaining optimal quality measures for quantitative association rules
|
NEUROCOMPUTING |
Artículo | 2015 |
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
|
INTEGRATED COMPUTER-AIDED ENGINEERING |
Ponencia | 2015 |
MOPNAR-BigData: un diseño MapReduce para la extracción de reglas de asociación cuantitativas en problemas de big data
|
XVI Conferencia Congreso de la Asociación Española de Inteligencia Artificial (CAEPIA) (2015), pp. 979-989. |
Artículo | 2014 |
Discovering gene association networks by multi-objective evolutionary quantitative association rules
|
JOURNAL OF COMPUTER AND SYSTEM SCIENCES |
Artículo | 2014 |
Discovering quantitative association rules: A novel approach based on evolutionary algorithms
|
AI COMMUNICATIONS |
Artículo | 2014 |
Selecting the best measures to discover quantitative association rules
|
NEUROCOMPUTING |
Ponencia | 2013 |
A sensitivity analysis for quality measures of quantitative association rules
|
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS |
Artículo | 2011 |
An evolutionary algorithm to discover quantitative association rules in multidimensional time series
|
SOFT COMPUTING |
Ponencia | 2011 |
Analysis of Measures of Quantitative Association Rules
|
Hybrid Artificial Intelligent Systems: 6th International Conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011, Proceedings, Part II |
Artículo | 2011 |
Evolutionary association rules for total ozone content modeling from satellite observations
|
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS |
Artículo | 2011 |
Extensiones para el Ciclo de Mejora Continua en la enseñanza e investigación de Ingeniería Informática
|
Revista de Enseñanza Universitaria |
Ponencia | 2011 |
Inferring gene-gene associations from quantitative association rules
|
International Conference on Intelligent Systems Design and Applications |
Ponencia | 2011 |
Mining Quantitative Association Rules In Microarray Data Using Evolutive Algorithms
|
ICAART 2011: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1 |
Ponencia | 2011 |
On the use of algorithms to discover motifs in DNA sequences
|
International Conference on Intelligent Systems Design and Applications |
Ponencia | 2010 |
Cis-cop: Multiobjective identification of cis-regulatory modules based on constrains
|
XV Congreso Español sobre Tecnologías y Lógica Fuzzy ESTYLF 2010: Huelva [Recurso electrónico] |
Ponencia | 2010 |
EVFUZZYSYSTEM: evolución de sistemas difusos para problemas de regresión multi-dimensionales
|
XV Congreso Español sobre Tecnologías y Lógica Fuzzy ESTYLF 2010: Huelva [Recurso electrónico] |
Artículo | 2010 |
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution
|
INTEGRATED COMPUTER-AIDED ENGINEERING |
Ponencia | 2009 |
Descubriendo Reglas de Asociación Numéricas entre Series Temporales
|
MINCODA 2009 : 1st International Workshop on Mining of Non-Conventional Data (Taller dentro de las Jornadas CAEPIA–TTIA 2009) (2009), pp. 16-24. |
Ponencia | 2009 |
Quantitative Association Rules Applied to Climatological Time Series Forecasting
|
INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING, PROCEEDINGS |