RESEARCH ON BURSA NONLINEAR 7-PARAMETER
TRANSFORMATION WITH PSO ALGORITHM
Yang Xing;Zhu Dadong;Zhao Gang ;and Li Zhiqing
Jiangsu Hydraulic Research Institute,Nanjing 210017
Abstract The 7parameter is the main parameter for space coordinate transformation,and the minor error of 7parameter could lead to large coordinate conversion deviances.In order to improve the computational accuracy of 7parameter,a mathematical model of Bursa 7parameter analysis based on the partical swarm optimization(PSO) algorithm was established.Compared with a least square method,the model can avoid effectively the matrix’s morbidity problem,difficulty of selecting initial values,the convergence of algorithm.Finally,the practical application shows that the model has many advantages such as high accuracy and can be adapted large rotation angle.
Key words ：
Bursa
7parameter
nonlinear transformation
PSO(Partical Swarn Oplimization)
3D coordinate
Received: 01 January 1900
Corresponding Authors:
Yang Xing
Cite this article:
Yang Xing,Zhu Dadong,Zhao Gang et al. RESEARCH ON BURSA NONLINEAR 7-PARAMETER
TRANSFORMATION WITH PSO ALGORITHM[J]. , 2012, 32(5): 86-90.
Yang Xing,Zhu Dadong,Zhao Gang et al. RESEARCH ON BURSA NONLINEAR 7-PARAMETER
TRANSFORMATION WITH PSO ALGORITHM[J]. jgg, 2012, 32(5): 86-90.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2012/V32/I5/86
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