基于BP_Adaboost的股票指数预测模型
Stock Composite Index Prediction Model Based on BP_Adaboost
本文首先对证券市场预测方面的研究进行回顾,并分析了近年来使用较多的神经网络模型的优缺点。其次,本文引入Adaboost算法,提出了能够将任意弱学习器进行组合改进为强学习器的BP_Adaboost方法。然后本文选取了沪深300指数数据进行模型实证,结果显示,BP_Adaboost模型的股指预测精度较单个BP神经网络明显提高。
Firstly, we carry out a review of the study of the stock market forecasting and analysis of the advantages and disadvantages of neural network model. Secondly, this paper introduces Adaboost algorithm, and proposes BP_Adaboost model which can be improve any weak learners to strong ones Then this article selects the CSI 300 Index historical data to empirical analysis,.The results show the prediction accuracy of BP_Adaboost model improved significantly compared to a single model of BP neural network.
梁德阳、牛明飞
财政、金融计算技术、计算机技术自动化技术、自动化技术设备
BP 神经网络daboost算法股票指数
BP Neural Networkdaboost AlgorithmStock Composte Index
梁德阳,牛明飞.基于BP_Adaboost的股票指数预测模型[EB/OL].(2013-12-30)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/201312-1064.点此复制
评论