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dc.contributor.authorYiğit, Fatihen_US
dc.contributor.authorEsnaf, Ş.en_US
dc.contributor.authorKavuş, B. Yalçınen_US
dc.date.accessioned2022-02-16T09:15:15Z
dc.date.available2022-02-16T09:15:15Z
dc.date.issued2021en_US
dc.identifier.citationYİĞİT, F., ESNAF, Ş., & KAVUŞ, B. Y. A Poisson-Regression, Support Vector Machine and Grey Prediction Based Combined Forecasting Model Proposal: A Case Study in Distribution Business. Turkish Journal of Forecasting, 5(2), 23-35.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12294/2956
dc.description.abstractDemand forecasting is a complicated task due to incomplete data and unpredictability. Accurate demand forecasting has a direct impact on the performance of a company. The goal of the study is to present a new two-stage combination model named Hybrid-2-Best, for accurate demand forecasting. The model combines three forecasting models in a single combined forecast. The Hybrid-2-Best model uses a two-stage algorithm to achieve better-performing forecasts. Case study showed that the proposed Hybrid-2-Best model performs the best forecast performance among other combination techniques and individual methods. Furthermore, GP integration in the first and second stages gives flexibility. Experimental results indicate that the proposed Hybrid-2-Best model is a promising alternative for sales demand forecasting. MAPE of the proposed model is 0,13. This is a good result and better than compared other models. Proposed model performed better than other compared models in MASE and MSE as wellen_US
dc.language.isoengen_US
dc.publisherJournalParken_US
dc.relation.ispartofTurkish Journal of Forecastingen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/*
dc.subjectGrey Predictionen_US
dc.subjectPoisson-Regressionen_US
dc.subjectSupport Vector Machineen_US
dc.subjectCombined Forecastingen_US
dc.subjectSales Demand Forecastingen_US
dc.titleA Poisson-Regression, Support Vector Machine and Grey Prediction Based Combined Forecasting Model Proposal : A Case Study in Distribution Businessen_US
dc.typearticleen_US
dc.departmentMühendislik ve Mimarlık Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.authorid0000-0002-7919-544Xen_US
dc.identifier.volume5en_US
dc.identifier.issue2en_US
dc.identifier.startpage23en_US
dc.identifier.endpage35en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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