GPS HEIGHT FITTING BASED ON CHAOS PARTICLE SWARM SUPPORT VECTOR MACHINE AND CONSIDERING EFFECT OF TERRAIN
Ji Zhangjian 1,2) ;Yuan Yunbin 1) ; and Sheng Chuanzhen 1,2)
1)Institute of Geodesy and Geophysics,Chinese Academy of Sciences,Wuhan 4300772)Graduate University of Chinese Academy of Science,Beijing 100049
Abstract The application of chaos particle swarm support vector machine in GPS height fitting is studied. Taking the impact of terrain on the height conversion into account, the terrain correction is introduced to the support vector machine model. Considering the blindness of manmade choice of parameters of SVM, a chaos particle swarm optimization theory is used to select the parameters of SVM. Compared with the traditional fitting methods, such as polynomial curved surface, multiface function BP neural network, this method is better.
Key words ：
SVM
chaos optimization
PSO
terrain correction
height anomaly
Received: 01 January 1900
Corresponding Authors:
Ji Zhangjian
Cite this article:
Ji Zhangjian,Yuan Yunbin ,and Sheng Chuanzhen. GPS HEIGHT FITTING BASED ON CHAOS PARTICLE SWARM SUPPORT VECTOR MACHINE AND CONSIDERING EFFECT OF TERRAIN[J]. , 2010, 30(2): 95-98.
Ji Zhangjian,Yuan Yunbin ,and Sheng Chuanzhen. GPS HEIGHT FITTING BASED ON CHAOS PARTICLE SWARM SUPPORT VECTOR MACHINE AND CONSIDERING EFFECT OF TERRAIN[J]. jgg, 2010, 30(2): 95-98.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2010/V30/I2/95
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