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基于EDP算法的股票价格预测

STOCK INDEX FORECASTING USING ESTIMATION OF DISTRIBUTION PROGRAMMING BASED ON BAYESIAN NETWORK
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摘要 股票价格预测一直是金融分析领域的一个重点和难题.目前,运用智能系统对股票市场进行预测的方法已经被广泛确立.本文提出了用基于贝叶斯网络的EDP算法进行股票预测的模型,相对于传统的预测方法,具有收敛速度快的特点,根据实验的仿真结果显示,该模型对于股票价格预测效果较好. Stock market analysis is one of the most important and hard problems in finance analysis field. Recently, the usage of intelligent systems for stock market prediction has been widely established. In this paper, estimation of distribution programming based on Bayesian network（EDP） algorithm is proposed, which is used for the Nasdaq- 100 index of Nasdaq Stock MarketSM and the S＆P CNX NIFTY stock index analysis. Experimental results show that EDP algorithm is effective and outperforms traditional algorithm for the stock index forecasting problems.
作者 潘萌 陈月辉 宋乐辉
机构地区 济南大学信息科学与工程学院
出处 《山东师范大学学报（自然科学版）》 CAS 2008年第4期13-16,共4页 Journal of Shandong Normal University(Natural Science)
基金 国家自然科学基金(60573065) 山东省自然科学基金(Y2007G33) 山东省重点学科基金资助项目
关键词 贝叶斯网络 EDP算法 股票价格预测 bayesian network estimation of distribution programming stock index forecasting
分类号 TP181 [自动化与计算机技术—控制理论与控制工程]
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参考文献12

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共引文献7

山东师范大学学报（自然科学版）
2008年 第4期

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