Perfil

González García,   Pedro

Pedro González es Doctor en Informática por la Universidad de Granada en 2008. En la actualidad, es profesor Titular de Universidad en la Universidad de Jaén, en el área de Lenguajes y Sistemas Informáticos del Departamento de Informática de la Universidad de Jaén. Sus líneas de investigación incluyen Descubrimiento de Subgrupos, minería de datos, algoritmos evolutivos, lógica difusa y aprendizaje descriptivo.

ID ORCID: 0000-0002-6733-3868

Publicaciones

a multiclustering evolutionary hyperrectangle-based algorithm

journal-article

doi   10.1007/s44196-023-00341-3

eid  

2023

clustering: an r library to facilitate the analysis and comparison of cluster algorithms

journal-article

doi   10.1007/s13748-022-00294-2

eid  

2023

a case of study with the clustering r library to measure the quality of cluster algorithms

book-chapter

doi   10.1007/978-3-031-15471-3_8

eid  

2022

a cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams

journal-article

doi   10.1016/j.eswa.2021.115419

eid   2-s2.0-85108447117

2021

a preliminary many objective approach for extracting fuzzy emerging patterns

conference-paper

doi   10.1007/978-3-030-57802-2_10

eid   2-s2.0-85091270095

2021

implementation of data stream classification neural network models over big data platforms

book-chapter

doi   10.1007/978-3-030-85099-9_22

eid  

2021

an analysis of technological frameworks for data streams

journal-article

doi   10.1007/s13748-020-00210-6

eid   2-s2.0-85087121536

2020

fepds: a proposal for the extraction of fuzzy emerging patterns in data streams

journal-article

doi   10.1109/TFUZZ.2020.2992849

eid   2-s2.0-85097343956

2020

e2pamea: a fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments

journal-article

doi   10.1016/j.neucom.2020.07.007

eid   2-s2.0-85089073247

2020

a big data approach for the extraction of fuzzy emerging patterns

journal-article

doi   10.1007/s12559-018-9612-7

eid   2-s2.0-85059583181

2019

study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments

journal-article

doi   10.1186/S41044-018-0038-8

eid  

2019

moea-efep: multi-objective evolutionary algorithm for extracting fuzzy emerging patterns

journal-article

doi   10.1109/TFUZZ.2018.2814577

eid   2-s2.0-85043463556

2018

improvement of subgroup descriptions in noisy data by detecting exceptions

journal-article

doi   10.1007/s13748-017-0131-7

eid   2-s2.0-85056104507

2018

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

a first approach to handle fuzzy emerging patterns mining on big data problems: the evaefp-spark algorithm

conference-paper

doi   10.1109/FUZZ-IEEE.2017.8015673

eid   2-s2.0-85030163364

2017

subgroup discovery with evolutionary fuzzy systems in r: the sdefsr package

journal-article

doi   10.32614/RJ-2016-048

eid   WOS:000395669800020

2016

fugepsd: fuzzy genetic programming-based algorithm for subgroup discovery

conference-paper

doi   10.2991/IFSA-EUSFLAT-15.2015.65

eid   WOS:000358581100065

2015

a fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans

journal-article

doi   10.1016/j.ins.2014.11.030

eid   WOS:000349590000011

2015

overview on evolutionary subgroup discovery: analysis of the suitability and potential of the search performed by evolutionary algorithms

journal-article

doi   10.1002/widm.1118

eid   2-s2.0-84894630936

2014

an evolutionary fuzzy system for the detection of exceptions in subgroup discovery

conference-paper

doi   10.1109/IFSA-NAFIPS.2013.6608378

eid   2-s2.0-84886571079

2013

mefes: an evolutionary proposal for the detection of exceptions in subgroup discovery. an application to concentrating photovoltaic technology

journal-article

doi   10.1016/j.knosys.2013.08.001

eid   2-s2.0-84901762374

2013

genetic lateral tuning for subgroup discovery with fuzzy rules using the algorithm nmeef-sd

journal-article

doi   10.1080/18756891.2012.685323

eid   WOS:000303573600009

2012

an analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery

journal-article

doi   10.1016/j.eswa.2012.04.029

eid  

2012

a preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery

conference-paper

doi   10.1109/FUZZ-IEEE.2012.6251182

eid   2-s2.0-84867608211

2012

an overview on subgroup discovery: foundations and applications

journal-article

doi   10.1007/s10115-010-0356-2

eid   2-s2.0-79961211866

2011

analysis of the impact of using different diversity functions for the subgroup discovery algorithm nmeef-sd

conference-paper

doi   10.1109/GEFS.2011.5949498

eid   2-s2.0-79961231858

2011

evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department

journal-article

doi   10.1007/s00500-010-0670-3

eid   2-s2.0-81155154250

2011

on the discovery of association rules by means of evolutionary algorithms

journal-article

doi   10.1002/widm.18

eid   2-s2.0-84866089077

2011

subgroup discovery in an e-learning usage study based on moodle

conference-paper

doi   10.1109/NWeSP.2011.6088221

eid   2-s2.0-83755206272

2011

evolutionary algorithms for subgroup discovery applied to e-learning data

conference-paper

doi   10.1109/EDUCON.2010.5492470

eid   2-s2.0-77954934620

2010

nmeef-sd: non-dominated multiobjective evolutionary algorithm for extracting fuzzy rules in subgroup discovery

journal-article

doi   10.1109/TFUZZ.2010.2060200

eid   2-s2.0-77957797485

2010

an analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery

conference-paper

doi   10.1109/FUZZY.2009.5277412

eid   2-s2.0-71249130061

2009

evolutionary algorithms for subgroup discovery in e-learning: a practical application using moodle data

journal-article

doi   10.1016/J.ESWA.2007.11.026

eid   WOS:000262178000068

2009

non-dominated multi-objective evolutionary algorithm based on fuzzy rules extraction for subgroup discovery

book

doi   10.1007/978-3-642-02319-4_69

eid   2-s2.0-70350650187

2009

subgroup discovery with linguistic rules

book

doi   10.1007/978-3-540-73723-0_21

eid   2-s2.0-35648944704

2008

multiobjective genetic algorithm for extracting subgroup discovery fuzzy rules

conference-paper

doi   10.1109/MCDM.2007.369416

eid   2-s2.0-34548760287

2007

evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing

journal-article

doi   10.1109/TFUZZ.2006.890662

eid   2-s2.0-34548285425

2007

multiobjective evolutionary induction of subgroup discovery fuzzy rules: a case study in marketing

conference-paper

doi   10.1007/11790853_27

eid   2-s2.0-33746414789

2006