High accuracy data representation via sequence of neural networks

Acta Geodaetica et Geophysica Hungarica

Volumn 38, Issue 3, 2003, Pages 337-343

  Palancz B ^a   Volgyesi L ^a  

^a BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

Author keywords

Geoid; Neural networks

Indexed keywords

COMPUTATIONAL METHODS; ERROR ANALYSIS; NEURAL NETWORKS; REGRESSION ANALYSIS;

DATA REPRESENTATION;

GEOPHYSICS;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; GEOID; MATHEMATICAL ANALYSIS;

HUNGARY;

EID: 0142009542     PISSN: 12178977     EISSN: None     Source Type: Journal    
DOI: 10.1556/AGeod.38.2003.3.4     Document Type: Article

References (10)

1. Barsi A 1999: Geodéziai és Kartográfia, 51, 12-18.
2. Freeman J A 1994: Simulating Neural Networks with Mathematica. Addison Wesley, New York
3. Haykin I 1999: Neural Networks: A Comprehensive Foundation. Second Edition, Macmillan, New York
4. Horváth G et al. 1998: Neural networks and their technical applications (in Hungarian). Mülegyetemi Kiadó, Budapest
5. Joberg S 2001: Neural Networks Package. 2001 Mathematica Developer Conference, Champain, IL, USA
6. Kenyeres A 1999: Phys. Cem. Earth (A), 24, 85-90.
7. Papp G, Kalmár J 1996: In: Proceedings of the 7th International Meeting on Alphine Gravimetry. Österreichische Beiträge zu Meteorologie und Geophysik, 95-96.
8. Tóth Gy, Rózsa Sz 2000: New Datasets and Techniques - an Improvement in the Hungarian Geoid Solution. Paper presented at Gravity, Geoid and Geodynamics Conference, Barf, Alberta, Canada
9. Tóth Gy, Rózsa Sz, Andritsanos V D, Ádám J, Tziavos I N 2000: Phys. Chem. Earth (A), 25, 47-52.
10. Veres G 2002: Geodézia és Kartográfia, 54, 25-30.