Cluster occurrence in the DbL_SHADE population

Viktorin, Adam; Šenkeřík, Roman; Pluháček, Michal; Kadavý, Tomáš

dc.title	Cluster occurrence in the DbL_SHADE population	en
dc.contributor.author	Viktorin, Adam
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Kadavý, Tomáš
dc.relation.ispartof	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
dc.identifier.isbn	978-1-5090-6017-7
dc.date.issued	2018
dc.citation.spage	1123
dc.citation.epage	1130
dc.event.title	2018 IEEE Congress on Evolutionary Computation, CEC 2018
dc.event.location	Rio de Janeiro
utb.event.state-en	Brazil
utb.event.state-cs	Brazílie
dc.event.sdate	2018-07-08
dc.event.edate	2018-07-13
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Institute of Electrical and Electronics Engineers Inc.
dc.identifier.doi	10.1109/CEC.2018.8477793
dc.relation.uri	https://ieeexplore.ieee.org/document/8477793
dc.subject	L-SHADE	en
dc.subject	DbL_SHADE	en
dc.subject	DBSCAN	en
dc.subject	Cluster	en
dc.subject	Differential Evolution	en
dc.subject	Population Diversity	en
dc.description.abstract	This paper deals with the Success-History based Adaptive Differential Evolution with Linear decrease in population size and Distance based adaptation of control parameters (DbL-SHADE). The algorithm is subject to the analysis of the population clustering via Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The CEC2015 benchmark set in three dimensional settings (10D, 30D and 50D) was used as a testbed for comparison of the population clustering between L-SHADE and DbL-SHADE algorithms and the results are reported and discussed. © 2018 IEEE.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1008351
utb.identifier.obdid	43878842
utb.identifier.scopus	2-s2.0-85056285966
utb.identifier.wok	000451175500144
utb.source	d-scopus
dc.date.accessioned	2019-01-03T12:31:47Z
dc.date.available	2019-01-03T12:31:47Z
dc.description.sponsorship	Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST (European Cooperation in Science Technology) [Action CA15140, Action IC1406]; A.I. Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin
utb.contributor.internalauthor	Viktorin, Adam
utb.contributor.internalauthor	Šenkeřík, Roman
utb.contributor.internalauthor	Pluháček, Michal
utb.contributor.internalauthor	Kadavý, Tomáš
utb.fulltext.affiliation	Adam Viktorin, Roman Senkerik, Michal Pluhacek, Tomas Kadavy Faculty of Applied Informatics Tomas Bata University in Zlin T. G. Masaryka 5555, 760 01 Zlin, Czech Republic {aviktorin, senkerik, pluhacek, kadavy}@utb.cz
utb.fulltext.dates	-
utb.wos.affiliation	[Viktorin, Adam; Senkerik, Roman; Pluhacek, Michal; Kadavy, Tomas] Tomas Bata Univ Zlin, Fac Appl Informat, TG Masaryka 5555, Zlin 76001, Czech Republic
utb.scopus.affiliation	Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics