DocumentCode
527450
Title
Static effect of MagnetoTellric data processed by neural network
Author
Gong Yu-Rong ; Tang Jing-tian ; Cai Jian-Hua
Author_Institution
Inst. of Info-Phys. & Geomatics Eng., Central South Univ., Changsha, China
Volume
3
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
1455
Lastpage
1458
Abstract
In the frequency domain, the static effect has a huge impact on the MagnetoTellric signal, it also has enormous impact on the conclusion of the deep electrical structure. Do a good deal with the static effect is very important to the analysis result. In this paper, adopt the neural networks algorithm which is called BP to remove the static effect. Simulated the model of geophysics by MATLAB box found that this way has a good effect to get rid of the static effect.
Keywords
backpropagation; geophysics; geophysics computing; magnetotellurics; neural nets; MATLAB box; MagnetoTellric signal; backpropagation; frequency domain; geophysics; neural network algorithm; static effect; Adaptation model; Artificial neural networks; Conductivity; Data models; Electric fields; Training; BP neural network; MT(MagnetoTelluric); neural network; static effect;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5582868
Filename
5582868
Link To Document