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Fuzzy Time Series: An Application in E-Commerce

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dc.contributor.authorKarasan, Ali
dc.contributor.authorSevim, Ismail
dc.contributor.authorCinar, Melih
dc.date.accessioned2026-06-27T14:05:26Z
dc.date.issued2017
dc.description.abstractIn this chapter, we are planning to make a comparison between conventional Time Series Models and Fuzzy Time Series Models by an application in an e-commerce company. Future sales of furniture will be predicted. The performance of different models and forecasting periods are going to be analyzed to discuss advantages and disadvantages of each method. MAE is chosen as performance indicators of each model and forecasting period combination. As a conclusion to this chapter, generic strategies for prediction in an e-commerce company will be formulated in consideration of these indicators.en
dc.description.urihttps://doi.org/10.4018/978-1-5225-0997-4.ch015
dc.identifier.doi10.4018/978-1-5225-0997-4.ch015
dc.identifier.eissn2327-3283
dc.identifier.endpage290
dc.identifier.isbn978-1-5225-0998-1; 978-1-5225-0997-4
dc.identifier.issn2327-3275
dc.identifier.startpage258
dc.identifier.urihttps://hdl.handle.net/20.500.14981/56867
dc.identifier.wos000416673400016
dc.language.isoeng
dc.publisherIGI GLOBAL
dc.relation.ispartofHANDBOOK OF RESEARCH ON INTELLIGENT TECHNIQUES AND MODELING APPLICATIONS IN MARKETING ANALYTICS
dc.subjectARTIFICIAL NEURAL-NETWORKS
dc.subjectFORECASTING ENROLLMENTS
dc.subjectMODELS
dc.subjectPRICES
dc.subjectSYSTEMS
dc.subjectBusiness & Economics
dc.subjectComputer Science
dc.subjectOperations Research & Management Science
dc.titleFuzzy Time Series: An Application in E-Commerce
dc.typeArticle; Book Chapter
dspace.entity.typePublication
local.import.sourceWOS

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