DOI QR코드

DOI QR Code

LSTM-based Sales Forecasting Model

  • Hong, Jun-Ki (Department of Computer Engineering, Pai Chai University)
  • Received : 2020.12.29
  • Accepted : 2021.03.04
  • Published : 2021.04.30

Abstract

In this study, prediction of product sales as they relate to changes in temperature is proposed. This model uses long short-term memory (LSTM), which has shown excellent performance for time series predictions. For verification of the proposed sales prediction model, the sales of short pants, flip-flop sandals, and winter outerwear are predicted based on changes in temperature and time series sales data for clothing products collected from 2015 to 2019 (a total of 1,865 days). The sales predictions using the proposed model show increases in the sale of shorts and flip-flops as the temperature rises (a pattern similar to actual sales), while the sale of winter outerwear increases as the temperature decreases.

Keywords

References

  1. M. S. No, H. N. Heo, Y. J. Choi, and H. S. Lee, "Survey on the Internet Usage 2019," Ministry of Science and ICT (MSIT) and Korea Internet and Security Agency (KISA), 2020.
  2. J. K. Hong, "Analysis of Sales Volume by Products According to Temperature Change Using Big Data Analysis," The Journal of Bigdata, vol. 4, no. 2, pp. 85-91, Dec. 2019. https://doi.org/10.36498/kbigdt.2019.4.2.85
  3. S. Thomassey, "Sales Forecasts in Clothing industry: The Key Success Factor of The Supply Chain Management," International Journal of Production Economics, vol. 128, no. 2, pp. 470-483, Dec. 2010. https://doi.org/10.1016/j.ijpe.2010.07.018
  4. W. K. Wong and Z. X. Guo, "A Hybrid Intelligent Model for Medium-term Sales Forecasting in Fashion Retail Supply Chains using Extreme Learning Machine and Harmony Search Algorithm," International Journal of Production Economics, vol. 128, no. 2, pp. 614-624, 2010. https://doi.org/10.1016/j.ijpe.2010.07.008
  5. T. M. Choi and B. Shen, "A System of Systems Framework for Sustainable Fashion Supply Chain Management in the Big Data Era," in Proc. of 2016 IEEE 14th International Conference on Industrial Informatics(INDIN), pp. 902-908, 2016.
  6. T. M. Choi, "Incorporating Social Media Observations and Bounded Rationality into Fashion Quick Response Supply Chains in the Big Data Era," Transportation Research Part E: Logistics and Transportation Review, vol. 114, pp. 386-397, June 2018. https://doi.org/10.1016/j.tre.2016.11.006
  7. Y. Zhang, C. Zhang, and Y. Liu, "An AHP-Based Scheme for Sales Forecasting in the Fashion Industry," Analytical Modeling Research in Fashion Business, pp. 251-267 May 2016.
  8. S. Ren, T. Choi, and N. Liu, "Fashion Sales Forecasting with a Panel Data-Based Particle-Filter Model," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 45, no. 3, pp. 411-421, Mar. 2015. https://doi.org/10.1109/TSMC.2014.2342194
  9. Y. Ni and F. Fan, "A Two-Stage Dynamic Sales Forecasting Model for The Fashion Retail," Expert Systems with Applications, vol. 38, no. 3, pp. 1529-1536, Mar. 2011. https://doi.org/10.1016/j.eswa.2010.07.065
  10. A. Aksoy, N. Ozturk, and E. Sucky, "A Decision Support System for Demand Forecasting in the Clothing Industry," International Journal of Clothing Science and Technology, vol. 24, no. 4, pp. 221-236. July 2012. https://doi.org/10.1108/09556221211232829
  11. N. Liu, S. Ren, T. M. Choi, C. L. Hui, and S. F. Ng, "Sales Forecasting for Fashion Retailing Service Industry: A Review," Mathematical Problems in Engineering, vol. 2013, pp. 1-9, Oct. 2013.
  12. K. F. Au, T. M. Choi, and Y. Yu, "Fashion Retail Forecasting by Evolutionary Neural Networks," International Journal of Production Economics, vol. 114, no. 2, pp. 615-630, Aug. 2008. https://doi.org/10.1016/j.ijpe.2007.06.013
  13. S. Thomassey and M. Happiette, "A Neural Clustering and Classification System for Sales Forecasting of New Apparel Items," Applied Soft Computing Journal, vol. 7, no. 4, pp. 1177-1187, Aug. 2007. https://doi.org/10.1016/j.asoc.2006.01.005
  14. W. K. Wong and Z. X. Guo, "A Hybrid Intelligent Model for Medium-term Sales Forecasting in Fashion Retail Supply Chains using Extreme Learning Machine and Harmony Search Algorithm," International Journal of Production Economics, vol. 128, no. 2, pp. 614-624, Dec. 2010. https://doi.org/10.1016/j.ijpe.2010.07.008
  15. Z. L. Sun, T. M. Choi, K. F. Au, and Y. Yu, "Sales Forecasting using Extreme Learning Machine with Applications in Fashion Retailing," Decision Support Systems, vol. 46, no. 1, pp. 411-419, Dec. 2008. https://doi.org/10.1016/j.dss.2008.07.009
  16. S. Hochreiter and J. Schmidhuber, "Long Short-Term Memory," Neural Computation, vol. 9, no. 8, pp. 1735-1780, Nov. 1997. https://doi.org/10.1162/neco.1997.9.8.1735
  17. I. Sutskever, O. Vinyals, and Q. V. Le, "Sequence to Sequence Learning with Neural Networks," in Proc. of Advanced Neural Information Process Systems, pp. 3104-3112, 2014.
  18. Q. Zhang, Y. Li, and Y. Hu, "An Encrypted Speech Retrieval Scheme Based on Long Short-Term Memory Neural Network and Deep Hashing," KSII Transactions on Internet and Information Systems, vol. 14, no. 6, pp. 2612-2633, June 2020. https://doi.org/10.3837/tiis.2020.06.016
  19. A. Graves and N. Jaitly, "Towards End-to-end Speech Recognition with Recurrent Neural Networks," in Proc. of the 31st International Conference on Machine Learning(ICML), vol. 32, no. 2, pp. 1764-1772, 2014.
  20. O. Vinyals, A. Toshev, S. Bengio, and D. Erhan, "Show and Tell: A Neural Image Caption Generator," in Proc. of IEEE Conference Computer Vision Pattern Recognition, pp. 3156-3164, 2015.
  21. A. Karpathy and L. Fei-Fei, "Deep Visual-Semantic Alignments for Generating Image Descriptions," in Proc. of IEEE Conference Computer Vision Pattern Recognition, pp. 3128-3137, 2015.
  22. J. Kim and K. Chung, "Prediction Model of User Physical Activity using Data Characteristicsbased Long Short-Term Memory Recurrent Neural Networks," KSII Transactions on Internet and Information Systems, vol. 13, no. 4, pp. 2060-2077, Apr. 2019. https://doi.org/10.3837/tiis.2019.04.018
  23. D. P. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," in Proc. of 3rd International Conference for Learning Representations, pp.1-15, May 2015.