软件导刊2019，Vol.18Issue(1)：28-33,226,7.DOI:10.11907/rjdk.181779
基于循环神经网络的金融数据预测系统
Financial Data Forecasting System Based on Recurrent Neural Network
摘要
Abstract
The purpose of financial forecasting is to analyze financial historical data, construct forecasting model, and forecast the trend of future data.This paper combines the latest in-depth learning results with financial forecasting systematically and creatively, and puts forward a method of forecasting the changes of financial data using cyclic neural network.Firstly, this paper introduces the breakthrough of artificial intelligence in recent years, designs the system based on RNN technology, realizes it by computer language, and then displays the predictive effect of the system through the experimental group, and evaluates the predictive accuracy of the system by depth learning related evaluation algorithm.According to the final experimental evaluation results, the scheme uses the cyclic neural network to learn and analyze historical data, and using the model to predict the future trend of financial data has certain reliability and accuracy, thus in-depth learning has development potential in financial forecasting.关键词
深度学习/神经网络/RNN/大数据/金融预测Key words
deep learning/neural network/RNN/big data/financial forecast分类
信息技术与安全科学引用本文复制引用
黄有为,高燕..基于循环神经网络的金融数据预测系统[J].软件导刊,2019,18(1):28-33,226,7.基金项目
常熟理工学院2018届本科毕业设计(论文)重点资助项目(cslg2018032) （论文）
