Abstract
Aiming at the price of commodity coal, this paper logically and comprehensively uses the factor analysis dimensionality reduction method, the time series analysis prediction method, and the AHP decision method. And finally constructed the ARIMA-AHP combined model. Combined with this model, we can use R, PYTHON, and other software to program the solution, and give a short-term accurate forecast of thermal coal prices in Qinhuangdao. The conclusions drawn from the study are the main influencing factors of coal price, the internal structure of coal price time series, and the weight ranking of uncertain influencing factors.
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