An ANFIS Based Vehicle Sales Forecasting Model Utilizing Feature Clustering and Genetic Algorithms

dc.contributor.authorŞaykol, Ediz
dc.contributor.authorYılmaz, Atınç
dc.contributor.authorKaya, Umut
dc.date.accessioned2024-03-13T09:52:21Z
dc.date.available2024-03-13T09:52:21Z
dc.date.issued2020
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractThe automotive sector is one of Turkey’s most important industries, and the developments in technology are affecting the automotive sector as well as the other sectors. The methods that have been used to date indicate that the use of AI should be increased when the demand forecasting applications take into account the developments in the industry. For this purpose, by using the data taken from the Automotive Distributors Association and Turkish Statistical Institute Internet pages, intuitive learning hybrid ANFIS method is used to forecast the sales in this study. A clustering scheme is first applied to group the features, and then the features are fed into genetic algorithms to improve the prediction model performance. The experiments show that the prediction performance of the proposed method is good when compared to existing related studies in the literature.en_US
dc.identifier.endpage154en_US
dc.identifier.issn1304-0448
dc.identifier.issn2148-1059
dc.identifier.issue1en_US
dc.identifier.startpage139en_US
dc.identifier.trdizinid325546en_US
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/325546
dc.identifier.urihttps://hdl.handle.net/20.500.12662/2576
dc.identifier.volume13en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofHavacılık ve Uzay Teknolojileri Dergisien_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAn ANFIS Based Vehicle Sales Forecasting Model Utilizing Feature Clustering and Genetic Algorithmsen_US
dc.typeArticleen_US

Dosyalar