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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