relation: https://khub.utp.edu.my/scholars/1673/
title: Forward modeling of seabed logging with controlled source electromagnetic method using radial basis function networks
creator: Arif, A.
creator: Asirvadam, V.S.
creator: Karsiti, M.N.
description: Forward modeling is an important step in processing data of seabed logging (SBL) with controlled source electromagnetic (CSEM) method to determine the location and dimension of a hydrocarbon layer under the seafloor. In this research, forward modeling was conducted using a radial basis function (RBF) network, which is an important type of artificial neural networks. To train this RBF network, a data set was generated using a simulation software: COMSOL Multiphysics. The network designed has 3 layers with 3 neurons in the input layer and 1 neuron in the output layer. The single hidden layer contained neurons whose number had been varied between 1 and 20 neurons. The performance comparison showed that the RBF network with 10 neurons in its hidden layer was the best to model SBL with CSEM method. © 2011 IEEE.
date: 2011
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Arif, A. and Asirvadam, V.S. and Karsiti, M.N.  (2011) Forward modeling of seabed logging with controlled source electromagnetic method using radial basis function networks.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857077958&doi=10.1109%2fNatPC.2011.6136385&partnerID=40&md5=506b933cb8572e42a20aef42f9c1eb50
relation: 10.1109/NatPC.2011.6136385
identifier: 10.1109/NatPC.2011.6136385