摘要
为克服线性经典平差的不足,对非线性最小二乘进行了研究,主要将遗传算法应用于非线性模型参数估计领域,并采用阻尼最小二乘法和高斯-牛顿法对同一观测数据进行了处理,且对解算结果进行了比较。
In order to overcome the shortcomings of the linear classic adjustment,we had study the nonlinear least square.Genetic algorithm was applied to the nonlinear model parameter estimating fields in this paper.We processed the same observation data with damping least square method and Gaussian-Newton method,and made a comparison to the computed results.
出处
《地理空间信息》
2013年第4期150-151,190,共2页
Geospatial Information
基金
国家自然科学基金资助项目(41261093)
