Universiti Teknologi Malaysia Institutional Repository

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

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.

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Abstract

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.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Mekatronik dan Kawalan Automatik)) - Universiti Teknologi Malaysia, 2015; Supervisor : Dr. Herman Wahid
Uncontrolled Keywords:artificial neural network (ANN), synthetic data, radial basis function
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:48835
Deposited By:INVALID USER
Deposited On:15 Nov 2015 00:22
Last Modified:30 Jun 2020 02:20

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