Time Series Analysis of Sales Quantity In An Automotive Company and Estimation By Artificial Neural Networks

Seher ARSLANKAYA; Vildan ÖZ

doi:https://doi.org/10.16984/saufenbilder.456518

Makale detayları

Time Series Analysis of Sales Quantity In An Automotive Company and Estimation By Artificial Neural Networks

Yazarlar:

Seher ARSLANKAYA | Vildan ÖZ

Ana Başlıklar:

İmalat

Dergi:

Sakarya University Journal of Science 2018 Vol.22 Issue 5, pp.1482-1492

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000557653

DOI:

https://doi.org/10.16984/saufenbilder.456518

Özet:

 


The automotive sector is an indicator sector that sheds light on the
economies of the countries. Demand forecasting in such an important sector, as
it is in every sector, is an important work topic. Two important problems of a
real production environment are uncertain demand and unbalanced production
times. These two parameters affect the semi-finished and finished product
inventory levels which lead to an increase in the total cost of the production
system. Demand forecasting is the estimation of how much consumers and services
they will demand in the future with the aid of variables. In this study,
automotive sector, one of the most important sectors of today, has been
estimated demand of sales quantities. Estimation results with Regression
Analysis (RA) and time series are compared with the estimation results made with
artificial neural networks.


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Makale detayları

Time Series Analysis of Sales Quantity In An Automotive Company and Estimation By Artificial Neural Networks

Yazarlar: Seher ARSLANKAYA | Vildan ÖZ

Ana Başlıklar: İmalat

Dergi: Sakarya University Journal of Science 2018 Vol.22 Issue 5, pp.1482-1492

Belge Tipi: Makale

Yayın Tarihi: 9/2018

Belge Dili: İngilizce

Document ID (Org No.): 2000557653

DOI: https://doi.org/10.16984/saufenbilder.456518

Sayı

Yazarlar:

Seher ARSLANKAYA | Vildan ÖZ

Ana Başlıklar:

İmalat

Dergi:

Sakarya University Journal of Science 2018 Vol.22 Issue 5, pp.1482-1492

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000557653

DOI:

https://doi.org/10.16984/saufenbilder.456518