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A time performance comparison of particle swarm optimization in mobile devices

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dc.title A time performance comparison of particle swarm optimization in mobile devices en
dc.contributor.author Beltrán-Prieto, Juan Carlos
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Torres Friás, Rubén
dc.contributor.author Escoto Hernández, Juan Luis
dc.relation.ispartof MATEC Web of Conferences 20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016)
dc.identifier.issn 2261-236X Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2016
utb.relation.volume 76
dc.event.title 20th International Conference on Circuits, Systems, Communications and Computers (CSCC)
dc.event.location Corfu
utb.event.state-en Greece
utb.event.state-cs Řecko
dc.event.sdate 2016-07-14
dc.event.edate 2016-07-17
dc.type conferenceObject
dc.language.iso en
dc.publisher EDP Sciences
dc.identifier.doi 10.1051/matecconf/20167604029
dc.relation.uri https://www.matec-conferences.org/articles/matecconf/abs/2016/39/matecconf_cscc2016_04029/matecconf_cscc2016_04029.html
dc.description.abstract This paper deals with the comparison of three implementations of Particle Swarm Optimization (PSO), which is a powerful algorithm utilized for optimization purposes. Xamarin, a cross-platform development software, was used to build a single C# application capable of being executed on three different mobile operating systems (OS) devices, namely Android, iOS, and Windows Mobile 10, with native level performance. Seven thousand tests comprising PSO evaluations of seven benchmark functions were carried out per mobile OS. A statistical evaluation of time performance of the test set running on three similar devices each running a different mobile OS is presented and discussed. Our findings show that PSO running on Windows Mobile 10 and iOS devices have a better performance in computation time than in Android. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007007
utb.identifier.scopus 2-s2.0-85016093930
utb.identifier.wok 000392332200106
utb.source d-wok
dc.date.accessioned 2017-07-25T08:54:38Z
dc.date.available 2017-07-25T08:54:38Z
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]; Grant Agency of the Czech Republic-GACR [588 P103/15/06700S]; Internal Grant Agency of Tomas Bata University in Zlin [IGA/CebiaTech/2016/007]
dc.rights Attribution 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Beltrán-Prieto, Juan Carlos
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.fulltext.affiliation Luis Antonio Beltrán Prieto 1,a , Zuzana Komínkova-Oplatková 1 , Rubén Torres Frías 2 and Juan Luis Escoto Hernández 2 1 Faculty of Applied Informatics, Department of Informatics and Artificial Intelligence, Tomas Bata University in Zlín, Nad Stráněmi 4511,76005 Zlín, Czech Republic 2 Department of Systems and Computing, Technological Institute of Celaya, Av. Tecnológico y A. García Cubas S/N, 38010, Celaya, México a Corresponding author: beltran_prieto@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme project No. LO1303 (MSMT-7778/2014) and also by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089, further it was supported by Grant Agency of the Czech Republic—GACR 588 P103/15/06700S and by Internal Grant Agency of Tomas Bata University in Zlin under the project No. IGA/CebiaTech/2016/007.
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Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International