基于可解释深度学习的中国煤炭价格驱动因素研究OACHSSCD

With the deepening transformation of China's energy structure,fluctuations in coal prices are increasingly influenced by the complex interactions of multiple nonlinear factors.Coal price volatility not only directly affects national energy security but also exerts a profound impact on macroeconomic operations and policy regulation.Therefore,systematic research is urgently needed.This study con-structs a GS-XGBoost-SHAP-based analytical framework to systematically identify the key driving fac-tors of coal price fluctuations from a nonlinear perspective and to uncover the nonlinear mechanisms underlying both individual and interactive variable effects.The results indicate that:the NEWC Austral-ian thermal coal price,Daqing crude oil price,BRENT crude oil price,economic growth,and economic policy uncertainty are the core variables influencing coal price volatility,confirming the"energy-econo-my-uncertainty"three-dimensional driving mechanism of price formation.The relationships between coal prices and key variables exhibit significant nonlinear and asymmetric characteristics,with positive driving effects being notably stronger than negative inhibitory effects.The interaction effects among variables are heterogeneous and display strong nonlinearity in coal price formation,with strong interactions primarily concentrated in the value ranges where key variables exert strong positive effects on coal prices.