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

nets4learning: a web platform for designing and testing ann/dnn models

journal-article

doi   10.3390/electronics13224378

eid  

2024

desreg: dynamic ensemble selection library for regression tasks

journal-article

doi   10.1016/j.neucom.2024.127487

eid  

2024

analysis of transformer model applications

book-chapter

doi   10.1007/978-3-031-40725-3_20

eid  

2023

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

nospcimen: a first approach to unsupervised discarding of empty photo trap images

book-chapter

doi   10.1007/978-3-031-43078-7_4

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

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

journal-article

doi   10.1007/s10462-017-9593-z

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

automatic time series forecasting with grnn: a comparison with other models

book

doi   10.1007/978-3-030-20521-8_17

eid   2-s2.0-85067499231

2019

automating autoencoder architecture configuration: an evolutionary approach

book

doi   10.1007/978-3-030-19591-5_35

eid   2-s2.0-85065895119

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

remedial-hwr: tackling multilabel imbalance through label decoupling and data resampling hybridization

journal-article

doi   10.1016/j.neucom.2017.01.118

eid   2-s2.0-85029575439

2019

predtoolsts: r package for streamlining time series forecasting

journal-article

doi   10.1007/s13748-019-00193-z

eid   2-s2.0-85067250925

2019

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

dealing with seasonality by narrowing the training set in time series forecasting with knn

journal-article

doi   10.1016/j.eswa.2018.03.005

eid   2-s2.0-85043460486

2018

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   2-s2.0-85042128332

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

on the impact of imbalanced data in convolutional neural networks performance

book

doi   10.1007/978-3-319-59650-1_19

eid   2-s2.0-85021778345

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   2-s2.0-84994174430

2017

recognition of activities in resource constrained environments; reducing the computational complexity

book

doi   10.1007/978-3-319-48799-1_8

eid   2-s2.0-85009786854

2016

estimating the maximum power delivered by concentrating photovoltaics technology through atmospheric conditions using a differential evolution approach

book

doi   10.1007/978-3-319-32034-2_23

eid   2-s2.0-84964007917

2016

multilabel classification: problem analysis, metrics and techniques

book

doi   10.1007/978-3-319-41111-8

eid   2-s2.0-85006335487

2016

on the impact of dataset complexity and sampling strategy in multilabel classifiers performance

book

doi   10.1007/978-3-319-32034-2_42

eid   2-s2.0-84964054564

2016

r ultimate multilabel dataset repository

book

doi   10.1007/978-3-319-32034-2_41

eid   2-s2.0-84964054493

2016

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   2-s2.0-84926643988

2015

addressing imbalance in multilabel classification: measures and random resampling algorithms

journal-article

doi   10.1016/j.neucom.2014.08.091

eid   2-s2.0-84930273620

2015

co<sup>2</sup>rbfn-cs: first approach introducing cost-sensitivity in the cooperative-competitive rbfn design

book

doi   10.1007/978-3-319-19258-1_31

eid   2-s2.0-84937400529

2015

mlsmote: approaching imbalanced multilabel learning through synthetic instance generation

journal-article

doi   10.1016/j.knosys.2015.07.019

eid   2-s2.0-84944354565

2015

quinta: a question tagging assistant to improve the answering ratio in electronic forums

conference-paper

doi   10.1109/EUROCON.2015.7313677

eid   2-s2.0-84961695915

2015

resampling multilabel datasets by decoupling highly imbalanced labels

conference-paper

doi   10.1007/978-3-319-19644-2-41

eid   2-s2.0-84932146148

2015

concurrence among imbalanced labels and its influence on multilabel resampling algorithms

book

doi   10.1007/978-3-319-07617-1_10

eid   2-s2.0-84902509247

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   2-s2.0-84907817318

2014

mlenn: a first approach to heuristic multilabel undersampling

book

doi   10.1007/978-3-319-10840-7-1

eid   2-s2.0-84906347859

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   2-s2.0-84907532927

2014

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

conference-paper

doi   10.1109/IJCNN.2013.6706973

eid   2-s2.0-84893601045

2013

a first approach to deal with imbalance in multi-label datasets

book

doi   10.1007/978-3-642-40846-5_16

eid   2-s2.0-84884913245

2013

characterization of concentrating photovoltaic modules by cooperative competitive radial basis function networks

journal-article

doi   10.1016/j.eswa.2012.09.016

eid   2-s2.0-84872038963

2013

a performance study of concentrating photovoltaic modules using neural networks: an application with co<sup>2</sup>rbfn

book

doi   10.1007/978-3-642-32922-7_45

eid   2-s2.0-84868286270

2013

improving multi-label classifiers via label reduction with association rules

book

doi   10.1007/978-3-642-28931-6_18

eid   2-s2.0-84858826037

2012

a summary on the study of the medium-term forecasting of the extra-virgen olive oil price

book

doi   10.1007/978-3-642-25274-7_27

eid   2-s2.0-81055147979

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   2-s2.0-79956151060

2011

intelligent systems in long-term forecasting of the extra-virgin olive oil price in the spanish market

book

doi   10.1007/978-3-642-13022-9_21

eid   2-s2.0-79551534856

2010

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   2-s2.0-75149139352

2010

a preliminary study on mutation operators in cooperative competitive algorithms for rbfn design

conference-paper

doi   10.1109/IJCNN.2010.5596330

eid   2-s2.0-79959410025

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

book

doi   10.1007/978-3-642-02478-8_94

eid   2-s2.0-68849096585

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

book

doi   2-s2.0-38049174812

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   2-s2.0-33847224122

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

book

doi   2-s2.0-25144519494

eid  

2003

optimizing rbf networks with cooperative/competitive evolution of units and fuzzy rules

book

doi   2-s2.0-84902140554

eid  

2001