[1]QIAN Xiao-shan,YANG Chun-hua.Improved gene expression programming algorithm tested by predicting stock indexes[J].CAAI Transactions on Intelligent Systems,2010,5(4):303-307.
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Improved gene expression programming algorithm tested by predicting stock indexes

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 4 Page number: 303-307 Column: 学术论文—人工智能基础 Public date: 2010-08-25
Title:
Improved gene expression programming algorithm tested by predicting stock indexes
Author(s):
QIAN Xiao-shan1; 2;  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
Keywords:
gene expression programming;  complexity analysis;  convergence analysis;  prediction in stockprice index
CLC:
TP18
DOI:
-
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. 
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