基于CCA-ELM模型的国产LNG出厂价格中短期预测研究OACHSSCDCSTPCD

This paper constructs a CCA-ELM model for LNG ex-factory price forecast,considering supply and demand fundamentals and non-fundamental factors.Supply and demand fundamentals include LNG production,sales volume,inventory,air temperature,and feedstock gas cost,while such alternative energy prices as crude oil,gasoline,diesel fuel,coal,as well as Northeast Asian natural gas spot prices belongs to non-fundamental influences factors.It conducts the typical correlation analysis to examine the extent to which each influencing factor contributes to the price.A CCA-ELM neural network prediction model is constructed using the weekly data of the 10 influencing factors,the historical series of LNG ex-factory prices and their influencing factors.10 influencing factors are strongly correlated with LNG ex-factory prices,LNG ex-factory prices in China are more influenced by the energy market and less influenced by supply and demand fundamentals,and the CCA-ELM model,which takes into account the historical data of LNG ex-factory price and the influencing factors,effectively improves the prediction method of time series neural networks as well as increases the prediction accuracy.