基于循环神经网络的金融数据预测系统

摘要

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.%金融预测旨在对金融历史数据进行分析, 构建预测模型, 并对未来数据走势作出预测.系统创新性地将最新的深度学习成果与金融预测相结合, 提出使用循环神经网络预测金融数据变化的方法.首先介绍了近几年人工智能的突破性成果, 以RNN相关技术为基础对系统进行设计, 然后通过实验组展示系统预测效果, 并对系统获得的结果数据, 使用深度学习相关评估算法评估其预测准确性.实验评估结果表明, 使用循环神经网络学习与分析历史数据, 并将其模型用于预测未来金融数据走势的方案具有较高的可靠性与准确性.因此, 深度学习在金融预测领域具有较大发展潜力.