Paper Title:
An Intelligent Modeling Method Based on Genetic Programming and Genetic Algorithm
  Abstract

This paper utilizes Genetic Programming(GP) and Genetic Algorithm(GA) to analyze experiment data. The purpose of this research is to establish a function model of the data. The core methodology of this research is using GP to get the approximate model first, and then optimizes the parameters and enhance the fitness value of the model by using GA. To validate this method, two examples are given: one is the reconstruction of permeability-strain equation of the rock in literature[1]; another example is the function search automatically of the wire cable isolator experiment data. In the process of programming of parse tree, this paper adopted a new way that different from three traditional methods, the parse tree is described by matrix of special size, more significantly, this new method makes the genetic operation of crossover and mutation intuitionstic, even the pellucid Matlab programming language could implement it.

  Info
Periodical
Advanced Materials Research (Volumes 33-37)
Edited by
Wei Yang, Mamtimin Geni, Tiejun Wang and Zhuo Zhuang
Pages
795-800
DOI
10.4028/www.scientific.net/AMR.33-37.795
Citation
J. Hu, X. N. Zhang, S. L. Xie, "An Intelligent Modeling Method Based on Genetic Programming and Genetic Algorithm", Advanced Materials Research, Vols. 33-37, pp. 795-800, 2008
Online since
March 2008
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Price
$32.00
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