渭南师范学院学报2019，Vol.34Issue(2)：87-96,10.
基于自适应萤火虫算法的BP神经网络股价预测
BP Neural Network Stock Price Prediction Based on Adaptive Firefly Algorithm
摘要
Abstract
The BP neural network shows a very strong ability in predicting nonlinear systems such as stock prices.However, there are also inherent flaws.In order to improve its prediction accuracy, first the firefly algorithm is improved and an adaptive firefly algorithm (SFA) is proposed, and then it is combined with BP.A BP neural network model based on self-adaptive firefly algorithm is established, and then stock price prediction can be carried out.Through the selected four stock data, the BP, FA-BP and SFABP models were simulated and compared with the prediction accuracy of the stock price.The results show that SFA-BP is significantly better than the other two models, and can effectively predict the stock price, which has a certain degree of practicality.关键词
萤火虫算法/BP神经网络/股票/股价预测Key words
firefly algorithm/BP neural network/stock/stock price forecast分类
信息技术与安全科学引用本文复制引用
刘园园,贺兴时..基于自适应萤火虫算法的BP神经网络股价预测[J].渭南师范学院学报,2019,34(2):87-96,10.基金项目
陕西省软科学研究计划项目:陕西企业自主创新及实现方式问题研究 (2014KRM2801) （2014KRM2801）
西安市教育科技重大招标项目:创新教师评价模式全面提升教师综合素质研究 (2015ZB-ZY04) （2015ZB-ZY04）
