Research Article
Year 2018,
Volume: 22 Issue: 5, 1482 - 1492, 01.10.2018
Abstract
References
- [1] Tozun, M.F., Premium Application in Dealership System: Example of Automotive Sector, Beykent University, Institute of Social Sciences, Department of Business Administration, M.Sc. Thesis,2017.
- [2] Karaca, K., Comparing the Methods Used in Vehicle Demand Forecasting, Istanbul Technical University, Department of Industrial Engineering, M.Sc. Thesis,2015.
- [3] Makridakis, S., Wheelwright, S.C. ve Hyndman, R.J. (1998). Forecasting:methods and applications. Third Edition. Wiley.
- [4] Yazıcıoğlu, N. Demand Forecasting with Artificial Intelligence, Uludağ University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2010.
- [5] Bolt, G., 1994. Market and sales forecasting : a total approach, Kogan Page, Londra.
- [6] Olgun, S. Demand Forecasting Methods in Supply Chain Management and Application of a Demand Forecasting Model Based on Artificial Intelligence, Istanbul University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2009.
- [7] Kılıç, G., Pamukkale University, Graduate School of Natural and Applied Sciences, Computer Engineering Department, Master Thesis, 2015.
- [8] Es, H. Turkey Net Energy Demand Forecasting with Artificial Neural Networks, Gazi University, Natural Sciences Institute, Department of Industrial Engineering, Master's Thesis, 2013.
- [9] Yan, X. ve Su, X.G. (2009). Linear Regression Analysis: The or yand Computing. First edition, World Scientific Publishing Company.
- [10] Hanke, J.E. ve Wichern, D.W.(2009). Business forecasting.Ninth Edition, International Edition. Pearson.
- [11] Yücesoy, M. Demand Estimation with Artificial Neural Networks in the Clean Sector, Istanbul Technical University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2011.
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Time Series Analysis of Sales Quantity In An Automotive Company and Estimation By Artificial Neural Networks
Abstract
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.
References
- [1] Tozun, M.F., Premium Application in Dealership System: Example of Automotive Sector, Beykent University, Institute of Social Sciences, Department of Business Administration, M.Sc. Thesis,2017.
- [2] Karaca, K., Comparing the Methods Used in Vehicle Demand Forecasting, Istanbul Technical University, Department of Industrial Engineering, M.Sc. Thesis,2015.
- [3] Makridakis, S., Wheelwright, S.C. ve Hyndman, R.J. (1998). Forecasting:methods and applications. Third Edition. Wiley.
- [4] Yazıcıoğlu, N. Demand Forecasting with Artificial Intelligence, Uludağ University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2010.
- [5] Bolt, G., 1994. Market and sales forecasting : a total approach, Kogan Page, Londra.
- [6] Olgun, S. Demand Forecasting Methods in Supply Chain Management and Application of a Demand Forecasting Model Based on Artificial Intelligence, Istanbul University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2009.
- [7] Kılıç, G., Pamukkale University, Graduate School of Natural and Applied Sciences, Computer Engineering Department, Master Thesis, 2015.
- [8] Es, H. Turkey Net Energy Demand Forecasting with Artificial Neural Networks, Gazi University, Natural Sciences Institute, Department of Industrial Engineering, Master's Thesis, 2013.
- [9] Yan, X. ve Su, X.G. (2009). Linear Regression Analysis: The or yand Computing. First edition, World Scientific Publishing Company.
- [10] Hanke, J.E. ve Wichern, D.W.(2009). Business forecasting.Ninth Edition, International Edition. Pearson.
- [11] Yücesoy, M. Demand Estimation with Artificial Neural Networks in the Clean Sector, Istanbul Technical University, Institute of Science and Technology, Department of Industrial Engineering, M.Sc. Thesis, 2011.
- [12] Haykin, S. O. (2008). Neural Networks and Learning Machines (3 edition.). New York: Pearson.
- [13] Fyfe, C. (2000). Artificial neural networks and information theory. University of Paisley. http://bit.ly/2yTVxIY accessed from.
There are 13 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Industrial Engineering |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | October 1, 2018 |
| Submission Date | August 31, 2018 |
| Acceptance Date | September 10, 2018 |
| Published in Issue | Year 2018 Volume: 22 Issue: 5 |
Cite
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