• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

LSTM-based Sales Forecasting Model

Vol. 15, No. 4, April 30, 2021
10.3837/tiis.2021.04.003, Download Paper (Free):


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.


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Cite this article

[IEEE Style]
J. Hong, "LSTM-based Sales Forecasting Model," KSII Transactions on Internet and Information Systems, vol. 15, no. 4, pp. 1232-1245, 2021. DOI: 10.3837/tiis.2021.04.003.

[ACM Style]
Jun-Ki Hong. 2021. LSTM-based Sales Forecasting Model. KSII Transactions on Internet and Information Systems, 15, 4, (2021), 1232-1245. DOI: 10.3837/tiis.2021.04.003.

[BibTeX Style]
@article{tiis:24521, title="LSTM-based Sales Forecasting Model", author="Jun-Ki Hong and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2021.04.003}, volume={15}, number={4}, year="2021", month={April}, pages={1232-1245}}