Inversion of quasi-3D DC resistivity imaging data using artificial neural networks-Reference-Cited by-同舟云学术

Inversion of quasi-3D DC resistivity imaging data using artificial neural networks

Published:2010-01-19 Issue:1 Volume:119 Page:27-40
ISSN:0253-4126
Container-title:Journal of Earth System Science
language:en
Short-container-title:J Earth Syst Sci

Author:

Neyamadpour Ahmad,Wan Abdullah W. A. T.,Taib Samsudin

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

http://link.springer.com/content/pdf/10.1007/s12040-009-0061-2.pdf

Reference34 articles.

1. Aristodemou E, Pain C, De Oliveira C, Goddard T and Harris C 2005 Inversion of nuclear well-logging data using neural networks; Geophys. Prospect. 53 103–120.

2. Battiti R 1992 First and second order methods for learning: Between steepest descent and Newton’s method; Neural Computation 4(2) 141–166.

3. Baum E and Hausler D 1989 what size net gives valid generalization? In: Advances in Neural Information Processing Systems I (ed.) D. Touretzky, 80–90. Morgan Kaufman.

4. Claerbout J F and Muir F 1973 Robust modeling with erratic data; Geophysics 38 826–844.

5. Cranganu C 2007 Using Artificial Neural Networks to predict the presence of overpressured Zones in the Anadarko Basin, Oklahoma; Pure Appl. Geophys. 164 2067–2081.

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