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dc.contributor.authorArsić, Aleksandraen
dc.contributor.authorTuba, Milanen
dc.contributor.authorJordanski, Milošen
dc.date.accessioned2020-05-22T08:46:08Z-
dc.date.available2020-05-22T08:46:08Z-
dc.date.issued2016-11-14en
dc.identifier.isbn978-1-509-00622-9en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/2778-
dc.description.abstractWireless sensor networks are increasingly important and active research topic because of their many practical uses. Localization problem in the wireless sensor networks is significant since the information collected without location is usually unusable. Often used approach to the localization problem is to post GPS receivers on a small number of anchor nodes and then to locate the other sensor nodes using received signal strength to estimate the distance between unknown nodes and anchor nodes. Estimating positions of sensor nodes is a hard optimization problem that can be successfully solved by stochastic metaheuristics. In this paper we adapted recent swarm intelligence fireworks algorithm for the wireless sensor networks localization problem and compared it to other algorithms from literature. Fireworks algorithm, especially its new version, enhanced fireworks algorithm, proved to be uniformly superior, considering all quality indicators.en
dc.publisherIEEE-
dc.relation.ispartof2016 IEEE Congress on Evolutionary Computation, CEC 2016en
dc.titleFireworks algorithm applied to wireless sensor networks localization problemen
dc.typeConference Paperen
dc.relation.conferenceIEEE Congress on Evolutionary Computation, CEC 2016; Vancouver Convention CentreVancouver; Canada; 24 July 2016 through 29 July 2016-
dc.identifier.doi10.1109/CEC.2016.7744302en
dc.identifier.scopus2-s2.0-85008255629en
dc.relation.firstpage4038en
dc.relation.lastpage4044en
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Paper-
item.grantfulltextnone-
crisitem.author.orcid0000-0002-8876-6283-
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