%O cited By 0; Conference of 2009 IEEE Student Conference on Research and Development, SCOReD2009 ; Conference Date: 16 November 2009 Through 18 November 2009; Conference Code:80411
%L scholars571
%J SCOReD2009 - Proceedings of 2009 IEEE Student Conference on Research and Development
%D 2009
%R 10.1109/SCORED.2009.5443293
%K Artificial Neural Network; Borehole logging; Geophysical inverse problems; Geophysical inversion; Multi layer perceptron; Synthetic data, Electric loads; Geophysics; Inverse problems; Mean square error; Models; Multilayer neural networks; Multilayers; Research, Well logging
%X This paper is a continuation report of the previous 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 multilayer perceptron (MLP). 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 MLP with a certain architecture. Finally, the trained MLP 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 0.016. ©2009 IEEE.
%P 93-96
%T Geophysical inversion using multilayer perceptron
%A A. Arif
%A V.S. Al Asirvadam
%A M.N. Bin Karsiti
%C Serdang