Using fuzzy time series to predict monthly cement production and comparing it to the traditional method
applied case study: Elmergib Cement Plant
DOI:
https://doi.org/10.59743/jbs.v39i2.353Keywords:
conventional time series, fuzzy time series, Chen model, cement production volumesAbstract
This study aims to find a suitable model for forecasting the production of a Libyan cement plant. Given the security and economic challenges Libya has faced in recent years, which have had a clear impact on production in general and cement production in particular, causing significant fluctuations and changes in production volume, the production chain becomes unstable. This makes the use of traditional time series methods for forecasting inaccurate and impractical. Therefore, we are compelled to use the Fuzzy Time Series (FST) method, also known as the Chen method, to forecast cement production volumes for 2024. This is based on the monthly production volume series for the period from January 2021 to November 2023. The production range was divided into 16 periods, and the time series data (cement production volume) was converted into fuzzy numbers, establishing fuzzy relationships. Production volumes for eleven months of 2023 were then forecasted based on the production series for 2021 and 2022 using both traditional and fuzzy time series methods. The forecasting performance was evaluated using the mean percentage absolute error (MAPE), mean absolute error (MAE), and root mean square error (RMSE). The results show that the fuzzy time series model outperforms the conventional time series model in terms of accuracy.
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