Research on coal price prediction model based on feature engineering
YANG Zhenqian
Abstract：Accurate prediction of coal price is of great significance to ensure national energy security and help realize the dual-carbon goal,for the problem that the accuracy of coal price prediction can still be further improved,the data of Qinhuangdao Q5500 power coal price and influencing factors in 2017-2023 are selected to determine the feature indexes of coal price prediction model based on the feature engineering analysis,and establish LSTM,RF,SVR and XGBoost model,according to the algorithm evaluation index to compare and analyze the performance of each model RMSE,MAE,MAPE,R2,the results show that the LSTM coal price prediction model has lower error,higher accuracy and optimal precision.
Keywords：coal price forecastsfeature engineeringLSTM modelPPMCCmachine learningalgorithm evaluation index
Publication Date：2024-11-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 30-37 )