现代信息科技2024，Vol.8Issue(6)：86-89,4.DOI:10.19850/j.cnki.2096-4706.2024.06.020
两种基于深度网络的股票价格预测方法研究
Research on Two Stock Price Forecasting Methods Based on Deep Network
摘要
Abstract
Stock is an important investment channel,how to forecast stock price more accurately is a hot research topic.Due to the complex characteristics of stock data,such as non-linearity,non-stationarity and before and after correlation,traditional stock price forecasting methods have reached the performance bottleneck.With the rise of Deep Learning methods,deep neural network forecast models such as LSTM and GRU have received great attention.Based on the historical trading data of Xiamen Port Stock and Shanghai Stock Index,LSTM and GRU models are used to forecast the closing price.The model evaluation is given by 5 indexes of MAE,MSE,RMSE,MAPE and R2.关键词
股票价格预测/LSTM模型/GRU模型Key words
stock price prediction/LSTM model/GRU model分类
信息技术与安全科学引用本文复制引用
孙震宇..两种基于深度网络的股票价格预测方法研究[J].现代信息科技,2024,8(6):86-89,4.基金项目
国家自然科学基金项目(62266055) （62266055）
