Sales forecasting for a Turkish paint producer: Artificial intelligence based methods versus multiple linear regression

Alp Ustundag*, Emre Cevikcan, Mehmet Serdar Kilinc

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

Sales forecasting has a great impact on facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best method of forecasting in all circumstances. Therefore, confidence in the accuracy of sales forecasts is derived by corroborating the results using two or more methods. This paper evaluates the relative performance of Linear Multiple Regression, Artificial Neural Networks and Adaptive Neuro Fuzzy Networks by applying them to the problem of sales forecasting for a Turkish paint producer firm. The results indicate that Adaptive Neuro Fuzzy Networks yields better forecasting accuracy in terms of Root Mean Square Error and Mean Absolute Deviation.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıWorld Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference
YayınlayanWorld Scientific Publishing Co. Pte Ltd
Sayfalar49-54
Sayfa sayısı6
ISBN (Basılı)981279946X, 9789812799463
DOI'lar
Yayın durumuYayınlandı - 2008
EtkinlikComputational Intelligence in Decision and Control - 8th International FLINS Conference - Madrid, Spain
Süre: 21 Eyl 200824 Eyl 2008

Yayın serisi

AdıWorld Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference

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???event.eventtypes.event.conference???Computational Intelligence in Decision and Control - 8th International FLINS Conference
Ülke/BölgeSpain
ŞehirMadrid
Periyot21/09/0824/09/08

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