Paper Title:
Some Improvements of Genetic Programming in Data Fitting
  Abstract

This paper proposed some improvement measures of Genetic Programming (GP) in data fitting, including developed new ways of crossover and mutation, improved the calculation efficiency greatly, and avoided the problem of parse tree expansion. The new adopted mutation method improved the problem of constant modification to some extent. Numerical simulation obtained a considerable good fitting and prediction precision.

  Info
Periodical
Advanced Materials Research (Volumes 201-203)
Edited by
Daoguo Yang, Tianlong Gu, Huaiying Zhou, Jianmin Zeng and Zhengyi Jiang
Pages
2536-2539
DOI
10.4028/www.scientific.net/AMR.201-203.2536
Citation
H. Jie, J. Q. Feng, D. L. Chen, "Some Improvements of Genetic Programming in Data Fitting", Advanced Materials Research, Vols. 201-203, pp. 2536-2539, 2011
Online since
February 2011
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Price
$32.00
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