Crude Oil Futures Price Index Forecast Based On GRU-CNN Model

This paper mainly studies a crude oil price prediction hybrid model(GRU-CNN)combining long short-term memory network(GRU)and convolutional neural network(CNN).The paper is divided into four chapters:Chapter one is the introduction,which briefly introduces the historical background and research significance of crude oil,and analyzes the research on crude oil price by research content and research methods.The second chapter is theory and design.This chapter mainly introduces some methods of neural network used in this paper,and leads to the research ideas of crude oil price in this paper.The third chapter mainly makes the empirical analysis of crude oil price prediction,gives some preliminary work such as data source and data pretreatment,and compares the combined prediction effect of various neural network algorithms,and obtains the best model combination through error analysis.The fourth chapter is the conclusion and suggestion.Through the analysis of the previous research on crude oil properties and the prediction results of crude oil price,the corresponding research conclusions are drawn,and the limitations of my current research are given,and the prospect is put forward.