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dc.contributor.authorMei, Bi
dc.contributor.authorWang, Xuguang
dc.contributor.authorWen, Quansi
dc.contributor.authorTang, Yong
dc.contributor.authorWang, Hao
dc.contributor.authorZhan, Choujun
dc.date.accessioned2019-06-07T07:38:30Z
dc.date.available2019-06-07T07:38:30Z
dc.date.created2019-05-28T12:42:06Z
dc.date.issued2019
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/11250/2600261
dc.description.abstractMobile Cloud Computing provides applications of cloud computing technology on mobile internet. In the era of 5G networks, Mobile Cloud Computing offers the possibility of heavy computational in parallel through different mobile terminals. This also offers us to use Mobile Cloud Computing to analyze fluctuations in user buying incentives over the course of a year. In various business scenarios, the purchase incentive of the public is often considered as being controlled by multiple factors and changes dramatically during holiday seasons. This paper proposed an evolutionary algorithm for monitoring purchase incentive of the public which can be distributed in Mobile Cloud Computing. In this work, we demonstrate that the public’s shopping behavior of a commodity is a consequence of a collective behavior propagating through a social network and can be modeled as a simple ODEs model. Then, based on this new model, we develop an extended Differential Evolution algorithm that is deployed on mobile terminals and combined with 5G network computing to estimate public incentives from historical sales datasets. Results suggest that this method can successfully monitor the public’s purchase incentive. Additionally, the overall purchase incentive changes dramatically during holiday seasons but fluctuates with similar patterns every year.nb_NO
dc.language.isoengnb_NO
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)nb_NO
dc.titleA Novel Algorithm for Estimating Purchase Incentive of The Public Based on Mobile Cloud Computingnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalIEEE Accessnb_NO
dc.identifier.doi10.1109/ACCESS.2019.2918206
dc.identifier.cristin1700857
dc.description.localcode© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedfalse
cristin.fulltextpreprint
cristin.qualitycode1


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