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Geophysical inversion using radial basis function

Arif, Agus and Asirvadam, Vijanth S. and Karsiti, M. N. (2010) Geophysical inversion using radial basis function. In: Intelligent and Advanced Systems (ICIAS), 2010 International Conference on.

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Abstract

This paper is a continuation report of a series of research on seabed logging (SBL). In this paper, it was shown that a certain geophysical inverse problem (such as one posed by SBL) can be solved using an important class of artificial neural networks, which is a radial basis function (RBF). To show this, several sets of synthetic data has been generated using some assumed models of a physical property (such as seabed resistivity) distribution. Then, these pairs of data and models were used to train a RBF with a certain architecture. Finally, the trained RBF was tested to do inversion with new data and produced a predicted model. The predicted model was reasonably close to the true model and the mean square error (MSE) between them was 0.065.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:4637
Deposited By: Dr Vijanth Sagayan Asirvadam
Deposited On:22 Nov 2012 02:55
Last Modified:19 Jan 2017 08:24

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