Demand Forecasting with Clustering and Artificial Neural Networks Methods: An Application for Stock Keeping Units-Reference-Cited by-同舟云学术

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Demand Forecasting with Clustering and Artificial Neural Networks Methods: An Application for Stock Keeping Units

Published:2021 Issue: Volume: Page:355-368
ISSN:2194-1009
Container-title:Springer Proceedings in Mathematics & Statistics
language:
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Author:

Ozturk Zehra Kamisli,Cetin Yesim,Isik Yesim,Cicek Zeynep Ídil Erzurum

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-78163-7_15

Reference33 articles.

1. Abolghasemi, M., Gerlach, R., Tarr, G., Beh, E.: Demand forecasting in supply chain: the impact of demand volatility in the presence of promotion (2019). arXiv preprint arXiv:1909.13084

2. Hofer, A.P., Halman, J.I.M.: The potential of layout platforms for modular complex products and systems. J. Eng. Design 16, 237–255 (2005)

3. Ren, S., Chan, H.L., Siqin, T.: Ann Oper Res (2019). https://doi.org/10.1007/s10479-019-03148-8

4. Arabie, P., Carroll, D., DeSarbo, W., Wind, J.: Overlapping clustering: a new method for product positioning. J. Market. Res. 18, 310–317 (1981)

5. Simpson, T.W., Siddique, Z., Jiao, J.: Product Platform And Product Family Design: Methods and Applications, 1st edn. Springer, New York, NY (2006)

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1. AutoML Approach to Stock Keeping Units Segmentation;Journal of Theoretical and Applied Electronic Commerce Research;2022-11-15

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