CONVERSION OF GPS HEIGHT BASED ON STANDARDIZATION MOMENTUM BP NEURAL NETWORK
Zhu Weidong ;and Li Quanhai
Department of Surveying and Geo-informatics，Tongji University，Shanghai 200092
Abstract When solving fitting elevation by using common momentum BP neural network algorithm there will be difference between the training samples in dimension. In order to improve the stability we standardized the samples and obtained the ideal results.It is shown that from the comparison among the results with the calculation methods by surface fitting, quadric surface fitting, and other neural network methods, the accuracy by using the standardization of BP neural network algorithm for elevation fitting is more reliable and stable.
Key words ：
momentum backpropagation neural network
geodetic height
normal height
elevation anomaly
standardization
Received: 01 January 1900
Corresponding Authors:
Zhu Weidong
Cite this article:
Zhu Weidong,and Li Quanhai. CONVERSION OF GPS HEIGHT BASED ON STANDARDIZATION MOMENTUM BP NEURAL NETWORK[J]. , 2010, 30(1): 123-125.
Zhu Weidong,and Li Quanhai. CONVERSION OF GPS HEIGHT BASED ON STANDARDIZATION MOMENTUM BP NEURAL NETWORK[J]. jgg, 2010, 30(1): 123-125.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2010/V30/I1/123
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