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New technology in shopping: forecasting electronic shopping with the use of a neuro-fuzzy system

Atsalakis Georgios

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URIhttp://purl.tuc.gr/dl/dias/7BC7D3AF-6001-4EDB-A963-FAF779931EC0-
Identifierhttps://www.tandfonline.com/doi/abs/10.1080/10454446.2014.1000445?journalCode=wfpm20-
Identifierhttps://doi.org/10.1080/10454446.2014.1000445-
Languageen-
Extent11 pagesen
TitleNew technology in shopping: forecasting electronic shopping with the use of a neuro-fuzzy systemen
CreatorAtsalakis Georgiosen
CreatorΑτσαλακης Γεωργιοςel
PublisherTaylor & Francisen
Content SummaryThis article presents the application of neuro-fuzzy techniques in forecasting a new technology in shopping. Neural networks have been used successfully to forecast time series due to their significant properties of treating nonlinear data with self-learning capability. However, neural networks suffer the difficulty of dealing with qualitative information and the “black box” syndrome that more or less limits their applications in practice. To overcome the drawbacks of neural networks, in this study, we proposed a fuzzy neural network that is a class of adaptive networks functionally equivalent to a fuzzy inference system. The results derived from the experiment based on electronic sales indicated that the suggested fuzzy neural network could be an efficient system to forecast a new technology in shopping. Experimental results also show that the neuro-fuzzy approach outperforms the other two conventional models (AR and ARMA). en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-04-27-
Date of Publication2017-
SubjectANFISen
SubjectElectronic shopping forecastingen
SubjectNeuro-fuzzy forecastingen
SubjectNew technology forecastingen
Bibliographic CitationG. Atsalakis, "New technology in shopping: forecasting electronic shopping with the use of a neuro-fuzzy system," J. Food Prod. Market., vol. 23, no. 5, pp. 522-532, Jul. 2017. doi: 10.1080/10454446.2014.1000445en

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