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Distributed artificial bee colony approach for connected appliances in smart home energy management system

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dc.contributor.authorBui, Khac-Hoai N.-
dc.contributor.authorAgbehadji, Israel E.-
dc.contributor.authorMillham, Richard-
dc.contributor.authorCamacho, David-
dc.contributor.authorJung, Jason J.-
dc.date.accessioned2021-05-20T08:40:34Z-
dc.date.available2021-05-20T08:40:34Z-
dc.date.issued2020-12-
dc.identifier.issn0266-4720-
dc.identifier.issn1468-0394-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/44039-
dc.description.abstractIn this study, we propose a computational intelligence model for the Internet of Things applications by applying the concept of swarm intelligence (SI) into connected devices. Particularly, decentralized management of smart home energy management system (HEMS) is taken into account in which connected appliances, by sharing information with each other, make the individual decisions for optimizing electricity prices of smart HEMS. Specifically, the study includes two main issues: (a) We propose a framework for decentralized management in smart HEMS; and (b) artificial bee colony (ABC) algorithm, a typical algorithm of SI techniques, has been applied for connected appliances in terms of communication and collaboration with each other to optimize the performance of the energy management system. Moreover, regarding the implementation, we develop and simulate a connected environment of smart home systems to evaluate the proposed approach. The simulation indicates the promising results in terms of optimizing the load balancing problem comparing with the conventional approach of the decentralized management system in smart home applications.-
dc.language영어-
dc.language.isoENG-
dc.publisherWILEY-
dc.titleDistributed artificial bee colony approach for connected appliances in smart home energy management system-
dc.typeArticle-
dc.identifier.doi10.1111/exsy.12521-
dc.identifier.bibliographicCitationEXPERT SYSTEMS, v.37, no.6-
dc.description.isOpenAccessN-
dc.identifier.wosid000597913400011-
dc.identifier.scopusid2-s2.0-85077897502-
dc.citation.number6-
dc.citation.titleEXPERT SYSTEMS-
dc.citation.volume37-
dc.type.docTypeArticle-
dc.publisher.location미국-
dc.subject.keywordAuthorartificial ant colony algorithm-
dc.subject.keywordAuthorconnected appliances-
dc.subject.keywordAuthordecentralized optimization method-
dc.subject.keywordAuthorInternet of Things-
dc.subject.keywordAuthorsmart home energy management system-
dc.subject.keywordAuthorswarm intelligence-
dc.subject.keywordPlusEDGE ANALYTICS-
dc.subject.keywordPlusINTERNET-
dc.subject.keywordPlusTHINGS-
dc.subject.keywordPlusIOT-
dc.subject.keywordPlusCOMMUNICATION-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusCHALLENGES-
dc.subject.keywordPlusALGORITHMS-
dc.subject.keywordPlusVEHICLES-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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소프트웨어대학 (소프트웨어학부)
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