Volume 18: Sustainable Energy Solutions for a Post-COVID Recovery towards a Better Future: Part I

Prediction of Oil Price Using LSTM and Prophet Lin Yao, Yuan Pu, Bo Qiu



With the fast development of the economy and industry, the demand for oil is increasing and the oil trade is becoming more and more frequent. And the oil price tends to be closely related to economic developments. So grasping the direction and trend of oil price is of great significance to the development of the world economy. In this paper, we selected the LSTM and Prophet algorithm to do the oil price’s prediction, to reach good results. RMSE and MAE are selected to represent the prediction’s precision. The RMSE and MAE values of LSTM are the smallest when setting the time_step as 10, which are 3.741 and 3.109 respectively. Values of Prophet are 3.212 and 2.471 respectively, which indicates that the prediction effect of Prophet is better.

Keywords Oil price prediction, LSTM, Prophet

Copyright ©
Energy Proceedings