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Polynomial Genetic Programming for Response Surface Modeling

Authors
Lee, K.H.Yeun, Y.S.Ruy, W.S.Yang, Y.S.
Issue Date
2002
Keywords
Function node stabilization; Genetic programming; Polynomial; Response surface
Citation
Proceedings of the Joint Conference on Information Sciences, v.6, pp 572 - 577
Pages
6
Journal Title
Proceedings of the Joint Conference on Information Sciences
Volume
6
Start Page
572
End Page
577
URI
https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9147
ISSN
0000-0000
Abstract
This paper deals with generating optimal polynomials using genetic programming (GP). Low order Taylor series are used to make the polynomial easily approximate nonlinear response surfaces or function. The overfitting problem is unavoidable because in real applications, the size of learning samples is minimal. This problem can be handled with the extended data set and function node stabilization method. Two examples are presented to demonstrate our method.
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