摘要
为克服线性化经典平差的不足,尝试利用遗传算法全局和局部搜索力强的优势,进行非线性最小二乘参数估计。对遗传算法涉及的六要素及其非线性估计的精度评定等作了研究和分析。最后通过算例验证了其处理非线性问题的有效性。
On the basis of the superiority of genetic algorithms whose ability of searching for the whole or the part is strong, nonlinear least squares estimation was used to overcome the disadvantage of classical least squares. 6 essential factors related to genetic algorithms and its precision evaluation of nonlinear estimation have been studied. The calculating results show that it is reasonable using the genetic algorithms to process the nonlinear estimation.
出处
《大地测量与地球动力学》
CSCD
北大核心
2006年第2期95-98,共4页
Journal of Geodesy and Geodynamics
基金
徕佧测绘基金项目
关键词
非线性最小二乘估计
遗传算法
六要素
适应度
精度评定
nonlinear least squares estimation, genetic algorithms,6 factors essential, fitness, precision evaluation
