Inversion of residual gravity anomalies using neural network

A new approach is presented in order to interpret residual gravity anomalies from simple geometrically shaped bodies such as horizontal cylinder, vertical cylinder, and sphere. This approach is mainly based on using modular neural network (MNN) inversion for estimating the shape factor, the depth, a...

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Bibliographic Details

Published in:	Arabian journal of geosciences Vol. 6; no. 5; pp. 1509 - 1516
Main Author:	Al-Garni, Mansour A.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer-Verlag 01.05.2013
Subjects:	Earth and Environmental Science Earth Sciences Original Paper Canada, Quebec ASW, Caribbean Sea, Greater Antilles, Cuba Simple-shaped bodies Neural network inversion Modular algorithm Gravity
ISSN:	1866-7511, 1866-7538
Online Access:	Get full text
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