Open AccessPrediction of Thermal Coal Prices in Qinhuangdao Port Based on ARIMA-AHP Model
Author(s) -
. Chu-Kaiwen,
. Zhu-Jiaming,
. Lu-Jiamin
Publication year - 2022
Publication title -
asian journal of economics, business and accounting
Language(s) - English
Resource type - Journals
ISSN - 2456-639X
DOI - 10.9734/ajeba/2022/v22i830590
Subject(s) - autoregressive integrated moving average , analytic hierarchy process , coal , python (programming language) , computer science , time series , ranking (information retrieval) , econometrics , goal programming , operations research , engineering , economics , artificial intelligence , machine learning , waste management , operating system
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.