Application of Bayesian regulation BP neural network to fit two-kind quasi-geoid

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/ Geomatics and Information Science of Wuhan University

Volumn 34, Issue 5, 2009, Pages

  Song, Lei ^a   Fang, Jian ^b   Zhou, Xuhua ^b   Huang, Teng ^a  

^a HOHAI UNIVERSITY   (China)

^b Wuhan National Laboratory for Optoelectronics   (China)

Author keywords

Bayesian regulation; BP neural network; Height anomaly; Quasi geoid

Indexed keywords

BAYESIAN REGULATION; BP NEURAL NETWORK; BP NEURAL NETWORKS; HEIGHT ANOMALY; NETWORK RESPONSE; POLYNOMIAL SURFACE FITTING; QUASI-GEOID;

BAYESIAN NETWORKS;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BAYESIAN ANALYSIS; GEOID; GPS; GRAVIMETRY; PRECISION;

EID: 65749103800     PISSN: 16718860     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (12)

1. Kiamehrand R, Sjoberg L E. Comparison of the qualities of recent global and local gravimetric geoid models in lran[J]. Studia Geophysica et Geodaetica, 2005, 49: 289-304
2. Kuroishi Y, Ando H, Fukuda Y. A new hybrid geoid model for Japan, GSIGEO2000[J]. Journal of Geodesy, 2002, 76:428-436
3. Hormik K. Approximation Capability of Multiplayer Feedforward Network [J]. Neural Networks, 1991(4): 251-257
4. MacKay D J C. Bayesian interpolation[J]. Neural Computation, 1992(4):415-447
5. Rapp R H. Use of potential coefficient models for geoid undulation determinations using a spherical harmonic representation of the height anomaly/geoid undulation difference[J]. Journal of Geodesy, 1997, 71:282-289