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A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study

C. A. Mitrea ; Nanyang Technological University, Singapore
C. K. M. Lee ; Nanyang Technological University, Singapore
Z. Wu ; Nanyang Technological University, Singapore

Puni tekst: engleski, pdf (809 KB) str. 19-24 preuzimanja: 3.613* citiraj
APA 6th Edition
Mitrea, C.A., Lee, C.K.M. i Wu, Z. (2009). A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study. International Journal of Engineering Business Management, 1 (2), 19-24. Preuzeto s https://hrcak.srce.hr/66717
MLA 8th Edition
Mitrea, C. A., et al. "A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study." International Journal of Engineering Business Management, vol. 1, br. 2, 2009, str. 19-24. https://hrcak.srce.hr/66717. Citirano 19.06.2021.
Chicago 17th Edition
Mitrea, C. A., C. K. M. Lee i Z. Wu. "A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study." International Journal of Engineering Business Management 1, br. 2 (2009): 19-24. https://hrcak.srce.hr/66717
Harvard
Mitrea, C.A., Lee, C.K.M., i Wu, Z. (2009). 'A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study', International Journal of Engineering Business Management, 1(2), str. 19-24. Preuzeto s: https://hrcak.srce.hr/66717 (Datum pristupa: 19.06.2021.)
Vancouver
Mitrea CA, Lee CKM, Wu Z. A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study. International Journal of Engineering Business Management [Internet]. 2009 [pristupljeno 19.06.2021.];1(2):19-24. Dostupno na: https://hrcak.srce.hr/66717
IEEE
C.A. Mitrea, C.K.M. Lee i Z. Wu, "A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study", International Journal of Engineering Business Management, vol.1, br. 2, str. 19-24, 2009. [Online]. Dostupno na: https://hrcak.srce.hr/66717. [Citirano: 19.06.2021.]

Sažetak
Forecasting accuracy drives the performance of inventory management. This study is to investigate and compare different forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive network with eXogenous inputs (NARX). Data used to forecast is acquired from inventory database of Panasonic Refrigeration Devices Company located in Singapore. Results have shown that forecasting with NN offers better performance in comparison with traditional methods.

Ključne riječi
ARIMA; Forecasting; Inventory; Neural Networks; Safety Stock

Hrčak ID: 66717

URI
https://hrcak.srce.hr/66717

Posjeta: 3.985 *