APPLICATION OF GENETIC ALGORITHM IN NONLINEAR REGRESSION MODEL GENERATING
Wang Suihui 1,2) ; and Pan Guorong 1,2)
1)Department of Surveying and Geomatics, Tongji University, Shanghai 2000922)Key Laboratory of Modern Engineering Surveying, SBSM, Shanghai 200092
Abstract On the basis of the principle which the function of high nonlinearity is not appropriate to linearize,the limitation of traditional methods in solving parameters of nonlinear regression estimation is analyzed. A new method based on genetic algorithm is proposed, which adopts uniform design means to combine genetic operator, conduct numerical experiments and then obtain optimal estimation of parameters of regression estimation. The results show that there is no need of good initial values of parameters when genetic algorithm is adopted, both the capability of global search and the robustness of genetic algorithms exceed that of traditional algorithms.
Key words ：
nonlinear regression
non-linearity
genetic algorithm
genetic operator
uniform design
Received: 01 January 1900
Corresponding Authors:
Wang Suihui
Cite this article:
Wang Suihui,and Pan Guorong. APPLICATION OF GENETIC ALGORITHM IN NONLINEAR REGRESSION MODEL GENERATING[J]. , 2008, 28(1): 59-64.
Wang Suihui,and Pan Guorong. APPLICATION OF GENETIC ALGORITHM IN NONLINEAR REGRESSION MODEL GENERATING[J]. jgg, 2008, 28(1): 59-64.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2008/V28/I1/59
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