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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Vydané v:	Arabian journal of geosciences Ročník 6; číslo 5; s. 1509 - 1516
Hlavný autor:	Al-Garni, Mansour A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer-Verlag 01.05.2013
Predmet:	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
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