电子器件2007，Vol.30Issue(4)：1387-1390,4.
遗传规划和最小二乘法在数据拟合中的应用
Application of Genetic Programming and Least Square Method on Data Fitting
夏炎 1田社平 1韦红雨 1王志武1
作者信息
- 1. 上海交通大学电子信息及电气工程学院,上海,200240
- 折叠
摘要
Abstract
A function that closely matches an unknown expression based on a finite set of sample data should be given in order to analyze and forecast data. Least square method is a commonly used method to solve the problem when the function expression is provided and it fails when no function expression can be provided. A new method for getting the fitting model by combining genetic programming and least square method is stated. Genetic programming can obtain the matched function expression by only giving the data points and the acceptable error. It can also simplify complex parts of the function. Furthermore, the parameters in the matched function expression are estimated by least square method to give more accurate fitting model. An example is given to prove the effectiveness of above method.关键词
最小二乘/遗传规划/数据拟合/非线性回归Key words
least squares/genetic programming/data fitting/nonlinear regression分类
信息技术与安全科学引用本文复制引用
夏炎,田社平,韦红雨,王志武..遗传规划和最小二乘法在数据拟合中的应用[J].电子器件,2007,30(4):1387-1390,4.
