Perfil

Rivera Rivas,   Antonio Jesús

Antonio J. Rivera es licenciado y dóctor en Informática por la Universidad de Granada, alcanzando estos títulos en 1995 y 2003 restpectivamente. Actualmente es profesor titular de la Universidad de Jaén en el área de Arquitectura y Tecnología de Computadores del departamento de Informática. Sus áreas de investigación de interés incluyen clasificación multietiqueta, conjuntos de datos desbalanceados, computación evolutiva, diseño de redes neuronales, predicción de series temporales o regresión funcional.

ID ORCID: 0000-0002-1062-3127

Publicaciones

xaire: an ensemble-based methodology for determining the relative importance of variables in regression tasks. application to a hospital emergency department

JOURNAL_ARTICLE

doi   10.1016/j.artmed.2023.102494

eid  

2023

time series forecasting by generalized regression neural networks trained with multiple series

JOURNAL_ARTICLE

doi   10.1109/ACCESS.2022.3140377

eid  

2022

Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

JOURNAL_ARTICLE

doi   10.1016/j.inffus.2019.07.004

eid   2-s2.0-85069698850

2020

Automatic Time Series Forecasting with GRNN: A Comparison with Other Models

BOOK_CHAPTER

doi   10.1007/978-3-030-20521-8_17

eid  

2019

A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy

BOOK

doi   10.1007/978-3-030-20521-8_23

eid   2-s2.0-85067454211

2019

Automating Autoencoder Architecture Configuration: An Evolutionary Approach

BOOK_CHAPTER

doi   10.1007/978-3-030-19591-5_35

eid  

2019

predtoolsTS: R package for streamlining time series forecasting

JOURNAL_ARTICLE

doi   10.1007/s13748-019-00193-z

eid   2-s2.0-85067250925

2019

Dealing with difficult minority labels in imbalanced mutilabel data sets

JOURNAL_ARTICLE

doi   10.1016/j.neucom.2016.08.158

eid   2-s2.0-85029618729

2019

A methodology for applying k-nearest neighbor to time series forecasting

JOURNAL_ARTICLE

doi   10.1007/s10462-017-9593-z

eid  

2019

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository

JOURNAL_ARTICLE

doi   10.1016/j.neucom.2018.02.011

eid   WOS:000428123200007

2018

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

JOURNAL_ARTICLE

doi   10.1016/j.neucom.2017.01.118

eid   WOS:000452306700012

2018

A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders

BOOK

doi   10.1007/978-3-030-03493-1_46

eid   2-s2.0-85057071604

2018

AEkNN: An autoencoder kNN–based classifier with built-in dimensionality reduction

JOURNAL_ARTICLE

doi   10.2991/ijcis.2018.125905686

eid   2-s2.0-85066340097

2018

Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass

JOURNAL_ARTICLE

doi   10.1016/j.compchemeng.2017.02.008

eid   2-s2.0-85014093400

2017

MEFASD-BD: Multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments - A MapReduce solution

JOURNAL_ARTICLE

doi   10.1016/j.knosys.2016.08.021

eid   WOS:000393006900007

2017

On the Impact of Imbalanced Data in Convolutional Neural Networks Performance

BOOK_CHAPTER

doi   10.1007/978-3-319-59650-1_19

eid   WOS:000432880600019

2017

R Ultimate Multilabel Dataset Repository

BOOK_CHAPTER

doi   10.1007/978-3-319-32034-2_41

eid   WOS:000389499600041

2016

On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance

BOOK_CHAPTER

doi   10.1007/978-3-319-32034-2_42

eid   WOS:000389499600042

2016

Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach

BOOK_CHAPTER

doi   10.1007/978-3-319-32034-2_23

eid   WOS:000389499600023

2016

Recognition of Activities in Resource Constrained Environments; Reducing the Computational Complexity

BOOK_CHAPTER

doi   10.1007/978-3-319-48799-1_8

eid   WOS:000389507400008

2016

Multilabel classification: Problem analysis, metrics and techniques

BOOK

doi   10.1007/978-3-319-41111-8

eid   2-s2.0-85006335487

2016

Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels

BOOK_CHAPTER

doi   10.1007/978-3-319-19644-2_41

eid   WOS:000363689900041

2015

A differential evolution proposal for estimating the maximum power delivered by CPV modules under real outdoor conditions

JOURNAL_ARTICLE

doi   10.1016/j.eswa.2015.02.032

eid   WOS:000355036900006

2015

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

JOURNAL_ARTICLE

doi   10.1016/j.knosys.2015.07.019

eid   WOS:000364249800028

2015

Addressing imbalance in multilabel classification: Measures and random resampling algorithms

JOURNAL_ARTICLE

doi   10.1016/j.neucom.2014.08.091

eid   WOS:000356196800002

2015

QUINTA: A Question Tagging Assistant to Improve the Answering Ratio in Electronic Forums

JOURNAL_ARTICLE

doi   WOS:000380463400014

eid  

2015

Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms

BOOK_CHAPTER

doi   WOS:000342836300010

eid  

2014

LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification

JOURNAL_ARTICLE

doi   10.1109/TNNLS.2013.2296501

eid   WOS:000343704900009

2014

Training algorithms for Radial Basis Function Networks to tackle learning processes with imbalanced data-sets

JOURNAL_ARTICLE

doi   10.1016/j.asoc.2014.09.011

eid   WOS:000344460600003

2014

MLeNN: A First Approach to Heuristic Multilabel Undersampling

BOOK_CHAPTER

doi   WOS:000345286100001

eid  

2014

A first analysis of the effect of local and global optimization weights methods in the cooperative-competitive design of RBFN for imbalanced environments

BOOK_CHAPTER

doi   WOS:000349557200266

eid  

2013

A First Approach to Deal with Imbalance in Multi-label Datasets

JOURNAL_ARTICLE

doi   WOS:000342910700016

eid  

2013

Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

JOURNAL_ARTICLE

doi   10.1016/j.eswa.2012.09.016

eid   WOS:000314737600018

2013

Improving Multi-label Classifiers via Label Reduction with Association Rules

OTHER

doi   WOS:000309173800018

eid  

2012

A Summary on the Study of the Medium-Term Forecasting of the Extra-Virgen Olive Oil Price

JOURNAL_ARTICLE

doi   WOS:000305319500027

eid  

2011

A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods

JOURNAL_ARTICLE

doi   10.1007/s10489-011-0284-1

eid   WOS:000290227300002

2011

GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems

JOURNAL_ARTICLE

doi   10.1016/j.ins.2009.12.020

eid   WOS:000275139300001

2010

A Preliminary Study on Mutation Operators in Cooperative Competitive Algorithms for RBFN Design

OTHER

doi   WOS:000287421403038

eid  

2010

Intelligent Systems in Long-Term Forecasting of the Extra-Virgin Olive Oil Price in the Spanish Market

OTHER

doi   WOS:000281604000021

eid  

2010

Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem

JOURNAL_ARTICLE

doi   10.1016/j.eswa.2009.11.056

eid   2-s2.0-77549084650

2010

EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design

JOURNAL_ARTICLE

doi   WOS:000270081200094

eid  

2009

An study on data mining methods for short-term forecasting of the extra virgin olive oil price in the Spanish market

CONFERENCE_PAPER

doi   10.1109/HIS.2008.132

eid   2-s2.0-55349083362

2008

CoEvRBFN: An approach to solving the classification problem with a hybrid cooperative-coevolutive algorithm

JOURNAL_ARTICLE

doi   WOS:000247839300040

eid  

2007

A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks

JOURNAL_ARTICLE

doi   10.1007/s00500-006-0128-9

eid   WOS:000244305200007

2007

Application of ANOVA to a cooperative-coevolutionary optimization of RBFNs

CONFERENCE_PAPER

doi   2-s2.0-25144441164

eid  

2005

Co-evolutionary algorithm for RBF by self-organizing population of neurons

JOURNAL_ARTICLE

doi   WOS:000185042000060

eid  

2003

Optimizing RBF networks with cooperative/competitive evolution of units and fuzzy rules

BOOK

doi   2-s2.0-84902140554

eid  

2001