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dc.contributor.authorÇakır, Mustafa
dc.contributor.authorAkbulut, Akhan
dc.contributor.authorÖnen, Yusuf Hatay
dc.date.accessioned2019-10-14T13:39:38Z
dc.date.available2019-10-14T13:39:38Z
dc.date.issued2019
dc.identifier52tr_TR
dc.identifier.urihttps://hdl.handle.net/11413/5410
dc.description.abstractIn our systematic mapping study, we examined 289 published works to determine which intelligent computing methods (e.g. Artificial Neural Networks, Machine Learning, and Fuzzy Logic) used by air-conditioning systems can provide energy savings and improve thermal comfort. Our goal was to identify which methods have been used most in research on the topic, which methods of data collection have been employed, and which areas of research have been empirical in nature. We observed the rules for literature reviews in identifying published works on databases (e.g. the Institute of Electrical and Electronics Engineers database, the Association for Computing Machinery Digital Library, SpringerLink, ScienceDirect, and Wiley Online Library) and classified identified works by topic. After excluding works according to the predefined criteria, we reviewed selected works according to the research parameters motivating our study. Results reveal that energy savings is the most frequently examined topic and that intelligent computing methods can be used to provide better indoor environments for occupants, with energy savings of up to 50%. The most common intelligent method used has been artificial neural networks, while sensors have been the tools most used to collect data, followed by searches of databases of experiments, simulations, and surveys accessed to validate the accuracy of findings.
dc.language.isoen_UStr_TR
dc.publisherSAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLANDtr_TR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectNeural Network
dc.subjectPerformance
dc.subjectComfort
dc.subjectSinir Ağı
dc.subjectPerformans
dc.subjectKonfor
dc.titleAnalysis of the use of computational intelligence techniques for air-conditioning systems: A systematic mapping study
dc.typeArticletr_TR
dc.relation.journalJournal Citation Reportstr_TR
local.journal.issue7-8tr_TR
local.journal.startpage1084tr_TR
local.journal.endpage1094tr_TR
dc.identifier.wos487111400034
dc.identifier.wos487111400034en
dc.identifier.scopus2-s2.0-85068309967
dc.identifier.scopus2-s2.0-85068309967en


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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States