Research on Cement Price Fluctuation Prediction Based on EEMD-ARIMA

Fan Yao, Hui Zeng (), Tongfei Liu and Yuwei Wu
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Fan Yao: Wuyi University
Hui Zeng: Wuyi University
Tongfei Liu: ZHUANGYAN Construction Group (Guangzhou) Co., Ltd.
Yuwei Wu: Hokkaido University

A chapter in Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate, 2023, pp 324-339 from Springer

Abstract: Abstract In this paper, we analyze cement price fluctuations and predict cement price. Taking the daily price data of ordinary silicate 42.5R (bulk) cement in Guangzhou from July 2013 to April 2022 as an example, we used Ensemble Empirical Mode Decomposition method to process cement price time series, then obtained from high to low frequency three parts of the intrinsic mode function (IMF) and the residuals (RES), from the perspective of influencing factors, explained the price fluctuation of cement. In the context of EEMD decomposition results, we made hierarchical forecasts and integrated final price value results, ARIMA model and RBF neural network prediction method are compared which can predict the cement price value more accurately. The result shows the sequence decomposed by EEMD has many advantages in simulating cement price prediction, based on the evaluation indicators of the prediction results such as MAE, RMSE and R2, it is determined that is a better combination method for predicting cement price fluctuations. All findings indicate that this paper provides a suitable approach for predicting the price fluctuation of civil engineering materials, and propose suggestions for project managers to deal with the risk of price fluctuations, try to prevent hidden cost problems caused by the cost deviation of engineering materials.

Keywords: Cement; Price fluctuation; EEMD; ARIMA; RBF neural network prediction (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-981-99-3626-7_26

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