Abstract: A prediction method for estimation of sales based on Prophet with a consideration of nonlinear events and conditions by a modified Optuna is proposed. Linear prediction does not work for a long-term sales prediction because purchasing actions are based on essentially nonlinear customers’ behavior. One of nonlinear prediction methods is the well-known Prophet. It, however, is still difficult to adjust the nonlinear parameters in the Prophet. To adjust the parameters, the Optuna is widely used. It, however, is not good enough for parameter tuning by the Optuna. Therefore, the Optuna is modified with a short-term moving mean and standard deviation of the sales for final prediction. More than that, specific event such as typhoon event is to be considered in the sales prediction. Through experiments with a real sales data, it is found the sensitivity of the parameters the upper window, lower window, event dates, etc. for the final sales and the effect of the Optuna is 11.73%. Also, it is found that the effect of the consideration of Covid-19 is about 2.4% meanwhile the effect of the proposed modified Optuna is around 3 % improvement of the prediction accuracy (from 80 % to 83 %).

Kohei Arai, Ikuya Fujikawa, Yusuke Nakagawa, Tatsuya Momozaki and Sayuri Ogawa, “Modified Prophet+Optuna Prediction Method for Sales Estimations” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130809

@article{Arai2022,
title = {Modified Prophet+Optuna Prediction Method for Sales Estimations},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130809},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130809},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Kohei Arai and Ikuya Fujikawa and Yusuke Nakagawa and Tatsuya Momozaki and Sayuri Ogawa}
}