Data fitting based on improved genetic programming
Pinchao Meng1, Weishi Yin1, Yanzhong Li2
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12A) 129-136
1Department of Applied Mathematics, Changchun University of Science and Technology, Changchun, China
2College of mathematics and statistics, Beihua University, Jilin, China
Traditional data fitting techniques usually require estimating basis function and they are specific for different application areas. Based on dynamic characteristics of genetic programming, a two-phase data fitting algorithm is proposed. In this algorithm, genetic programming is used to optimize model structure and Least Square method is applied to estimate parameters. Proposed algorithm is tested for different types of data fitting. Not only can this algorithm be applied in different areas, but also it is of high efficiency and accuracy