[1]钱晓山,阳春华.改进基因表达式编程在股票中的研究与应用[J].智能系统学报,2010,5(04):303-307.
 QIAN Xiao-shan,YANG Chun-hua.Improved gene expression programming algorithm tested by predicting stock indexes[J].CAAI Transactions on Intelligent Systems,2010,5(04):303-307.
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改进基因表达式编程在股票中的研究与应用(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第5卷
期数:
2010年04期
页码:
303-307
栏目:
出版日期:
2010-08-25

文章信息/Info

Title:
Improved gene expression programming algorithm tested by predicting stock indexes
文章编号:
1673-4785(2010)04-0303-05
作者:
钱晓山12阳春华1
1.中南大学 信息科学与工程学院,湖南 长沙 410083;
 2.宜春学院 物理科学与工程技术学院,江西 宜春336000
Author(s):
QIAN Xiao-shan12 YANG Chun-hua1
1. School of Information Science and Engineering, Central South University, Changsha 410083, China;
2. Physical Science and Technology College, Yichun University, Yichun 336000, China
关键词:
基因表达式编程复杂度分析收敛性分析股票指数预测
Keywords:
gene expression programming complexity analysis convergence analysis prediction in stockprice index
分类号:
TP18
文献标志码:
A
摘要:
介绍了基因表达式编程方法的基本原理,针对股票指数分析与预测问题,在经典的GEP算法基础上,提出了一种基于动态变异算子的改进的GEP算法——IGEP(improved GEP)算法.动态变异算子随着进化代数和染色体所含基因数目不同而变化,从而加快了GEP的收敛速度和精确度.还对算法进行了复杂度和收敛性分析.最后设计了一种基于IGEP的股票指数分析与预测算法,数值实验结果表明该算法优越于经典GEP算法,非常有效且具有较广泛的通用性.
Abstract:
The authors reviewed basic principles of gene expression programming (GEP). On that basis, an improved GEP algorithm, or IGEP, was created, based on a dynamic mutation operator. The dynamic mutation operator changed with the gene number of the genome and the number of evolutionary generations. The complexity and convergence properties of the algorithm were investigated. The new IGEP was used to predict stockmarket indexes. Simulation results indicated that the IGEPbased model is more accurate than the classical GEPbased model. 

参考文献/References:

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[10]段磊,唐常杰,左劼,等.基于基因表达式编程的抗噪声数据的函数挖掘方法[J].计算机研究与发展,2004,41(10):16841689.
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相似文献/References:

[1]钱晓山,阳春华.基于GEP的最小二乘支持向量机模型参数选择[J].智能系统学报,2012,7(03):225.
 QIAN Xiaoshan,YANG Chunhua.A parameter selection method of a least squares support vector machine based on gene expression programming[J].CAAI Transactions on Intelligent Systems,2012,7(04):225.
[2]彭昱忠,元昌安,李洁,等.个体最优共享GEP算法及其气象降水数据预测建模[J].智能系统学报,2016,11(3):401.[doi:10.11992/tis.201603035]
 PENG Yuzhong,YUAN Changan,LI Jie,et al.Individual optimal sharing GEP algorithm and its application in forecast modeling of meteorological precipitation[J].CAAI Transactions on Intelligent Systems,2016,11(04):401.[doi:10.11992/tis.201603035]

备注/Memo

备注/Memo:
收稿日期:2009-02-15.
基金项目:国家自然科学基金资助项目(60634020,60874069, 60804037);国家“863”计划资助项目(2006AA04Z181).
通信作者:钱晓山.E-mail:qianxiaoshan@126.com.
作者简介:
钱晓山,男,1980年生,讲师,博士研究生,主要研究方向为复杂工业过程建模、优化控制.
阳春华,女,1965年生,教授,博士生导师,享受国家政府特殊津贴,教育部新世纪优秀人才,获“湖南省青年科技奖”、“湖南省十大杰出女性”,主要研究方向为复杂工业过程建模、优化控制、智能信息处理.
更新日期/Last Update: 2010-09-20