Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression

In this study, a Multi-Layer Perceptron Neural Network and Multiple Regression techniques are used to estimate airwaves associated with shallow water Controlled-Source Electro-Magnetic (CSEM) data. Both techniques are appropriate for the development of estimation models. However, multiple regression...

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Main Authors: Abdulkarim, M., Ahmad, W.F.W., Ansari, A., Nyamasvisva, E.T., Shafie, A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31236 /
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938772012&doi=10.1109%2fICCOINS.2014.6868367&partnerID=40&md5=3ac022e89cf2d912ca20f73818e47b26
http://eprints.utp.edu.my/31236/
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spelling utp-eprints.312362022-03-25T09:03:42Z Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression Abdulkarim, M. Ahmad, W.F.W. Ansari, A. Nyamasvisva, E.T. Shafie, A. In this study, a Multi-Layer Perceptron Neural Network and Multiple Regression techniques are used to estimate airwaves associated with shallow water Controlled-Source Electro-Magnetic (CSEM) data. Both techniques are appropriate for the development of estimation models. However, multiple regression models make some assumptions about the underlying data. These assumptions include independence, normality and homogeneity of variance. Conversely, neural network based models are not constrained by such assumptions. The performance of the two techniques is calculated based on coefficient of determination (R2) and mean square error (MSE). The results indicate that MLP produced better estimate for the airwaves with MSE of 0.0113 and R2 of 0.9935. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938772012&doi=10.1109%2fICCOINS.2014.6868367&partnerID=40&md5=3ac022e89cf2d912ca20f73818e47b26 Abdulkarim, M. and Ahmad, W.F.W. and Ansari, A. and Nyamasvisva, E.T. and Shafie, A. (2014) Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression. In: UNSPECIFIED. http://eprints.utp.edu.my/31236/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description In this study, a Multi-Layer Perceptron Neural Network and Multiple Regression techniques are used to estimate airwaves associated with shallow water Controlled-Source Electro-Magnetic (CSEM) data. Both techniques are appropriate for the development of estimation models. However, multiple regression models make some assumptions about the underlying data. These assumptions include independence, normality and homogeneity of variance. Conversely, neural network based models are not constrained by such assumptions. The performance of the two techniques is calculated based on coefficient of determination (R2) and mean square error (MSE). The results indicate that MLP produced better estimate for the airwaves with MSE of 0.0113 and R2 of 0.9935. © 2014 IEEE.
format Conference or Workshop Item
author Abdulkarim, M.
Ahmad, W.F.W.
Ansari, A.
Nyamasvisva, E.T.
Shafie, A.
spellingShingle Abdulkarim, M.
Ahmad, W.F.W.
Ansari, A.
Nyamasvisva, E.T.
Shafie, A.
Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
author_sort Abdulkarim, M.
title Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
title_short Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
title_full Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
title_fullStr Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
title_full_unstemmed Airwaves estimation in shallow water CSEM data: Multi-layer perceptron versus multiple regression
title_sort airwaves estimation in shallow water csem data: multi-layer perceptron versus multiple regression
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938772012&doi=10.1109%2fICCOINS.2014.6868367&partnerID=40&md5=3ac022e89cf2d912ca20f73818e47b26
http://eprints.utp.edu.my/31236/
_version_ 1741197540375658496
score 11.62408

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