摘要
线性模型回归系数的一些稳健估计如LMS、LQS、LTS、LTA的应用越来越广泛,然而它们的精确计算依赖于NP难题,在遇到高维大规模数据集时不可能在较短时间内得到精确解.为尽快得到较高精度的近似解,提出了求解线性模型的稳健参数估计的整数编码遗传算法,通过计算机模拟试验验证了算法可以更快地找出全局最优解.
The linear regression coefficient of some robust estimation such as LMS,LTS, LTA has been widely applied,but their exact calculation depends on the NP problem.The exact solutions for large high dimensional data set can＇t compute in a reasonable time.To get more accurate results as soon as possible,the approximate solution using integer-coded genetic algorithm for solving linear model estimation is introduced.The computer simulation shows that the algorithm is correct and effective.
出处
《数学的实践与认识》
CSCD
北大核心
2011年第1期123-128,共6页
Mathematics in Practice and Theory
基金
河北省自然科学基金(A2011408006)
关键词
整数编码遗传算法
稳健估计
线性模型
integer-coded genetic algorithm
robust estimation
linear model
