Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques

The purpose of this study is to investigate the application of artificial neural network (ANN) in solving two dimensional Direct Current (DC) resistivity mapping for subsurface investigation. Neural network algorithms were proposed based on radial basis function (RBF) model and multi-layer perceptro...

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Main Author: Othman, Mohd. Hakimi
Format: Thesis
Language:English
Published: 2015
Subjects:
Online Access:http://eprints.utm.my/48835/25/MohdHakimiOthmanMFKE2014.pdf
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author Othman, Mohd. Hakimi
author_facet Othman, Mohd. Hakimi
author_sort Othman, Mohd. Hakimi
collection ePrints
description The purpose of this study is to investigate the application of artificial neural network (ANN) in solving two dimensional Direct Current (DC) resistivity mapping for subsurface investigation. Neural network algorithms were proposed based on radial basis function (RBF) model and multi-layer perceptron (MLP) model. Conventional approach of least square (LS) method was used as the benchmark and comparison for the proposed algorithm. In order to train the proposed algorithm, several synthetic data were generated using RES2DMOD software based on hybrid Wenner-Schlumberger configurations. Results were compared between the proposed algorithm and least square method in term of its effectiveness and error variations to actual values. It was discovered that the proposed algorithms have better performance in term of effectiveness and have minimum error difference to actual model as compared to least square method. Simulations result demonstrated that proposed algorithm can solve the inverse problem and can be illustrated by graphical means.
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spelling utm.eprints-488352020-06-30T02:20:07Z http://eprints.utm.my/48835/ Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques Othman, Mohd. Hakimi TK Electrical engineering. Electronics Nuclear engineering The purpose of this study is to investigate the application of artificial neural network (ANN) in solving two dimensional Direct Current (DC) resistivity mapping for subsurface investigation. Neural network algorithms were proposed based on radial basis function (RBF) model and multi-layer perceptron (MLP) model. Conventional approach of least square (LS) method was used as the benchmark and comparison for the proposed algorithm. In order to train the proposed algorithm, several synthetic data were generated using RES2DMOD software based on hybrid Wenner-Schlumberger configurations. Results were compared between the proposed algorithm and least square method in term of its effectiveness and error variations to actual values. It was discovered that the proposed algorithms have better performance in term of effectiveness and have minimum error difference to actual model as compared to least square method. Simulations result demonstrated that proposed algorithm can solve the inverse problem and can be illustrated by graphical means. 2015-01 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/48835/25/MohdHakimiOthmanMFKE2014.pdf Othman, Mohd. Hakimi (2015) Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:87864
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Othman, Mohd. Hakimi
Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title_full Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title_fullStr Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title_full_unstemmed Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title_short Two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
title_sort two dimensional direct current resistivity mapping for subsurface investigation using computational intlligence techniques
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/48835/25/MohdHakimiOthmanMFKE2014.pdf
work_keys_str_mv AT othmanmohdhakimi twodimensionaldirectcurrentresistivitymappingforsubsurfaceinvestigationusingcomputationalintlligencetechniques