计算机工程与应用Issue(20)：139-143,5.DOI:10.3778/j.issn.1002-8331.1312-0250
基于改进极限学习机算法的股票价格在线预测
Online prediction of stock price based on improved extreme learning machine
摘要
Abstract
In order to conduct fast and accurate online prediction of stock price, a novel online prediction model of stock price based on Improved Extreme Learning Machine(IELM)algorithm is proposed. Cholesky factorization is introduced into Extreme Learning Machine(ELM)and weight can update based on sequential input new samples, and improve com-putational efficiency, and then simulation experiment is carried out on shares(601328). The results show that the pro-posed model can improve computational efficiency and improve prediction precision of stock price, so the proposed model can be used in stock price online prediction.关键词
股票价格/极限学习机/在线预测/网络权值Key words
stock price/Extreme Learning Machine(ELM)/online prediction/network weight分类
信息技术与安全科学引用本文复制引用
陆玉,张华..基于改进极限学习机算法的股票价格在线预测[J].计算机工程与应用,2014,(20):139-143,5.基金项目
阜阳职业技术学院校级科研课题（No.2013JKYXM11）。 （）
