An Improved Gene Expression Programming for Solving Inverse Problem

Author

Zhang, Kejun ; Hu, Yuxia ; Liu, Gang

Author_Institution

Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3371

Lastpage

3375

Abstract

The basic principle of gene expression programming (GEP) is introduced in this paper. An improved GEP algorithm called IGEP based on dynamic mutation operator which dealing with the inverse problem of parameter identification of complex function is presented, the algorithm complexity of the IGEP was given in the paper, furthermore, many simulation results show that the models set up by the paper are better than the models set up by classic GEP. A future study will consider the effects of applying IGEP to the inverse problem which sensitive to the time period

Keywords

computational complexity; dynamic programming; genetic algorithms; inverse problems; parameter estimation; algorithm complexity; complexity analysis; dynamic mutation operator; gene expression programming; inverse problem; parameter identification; Algorithm design and analysis; Computer science; Digital art; Educational institutions; Gene expression; Genetic mutations; Genetic programming; Genomics; Inverse problems; Parameter estimation; Complexity analysis; Gene Expression Programming (GEP); Inverse problem; Parameters identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712993

Filename

1712993