Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon

The main objective of this project is to introduce a technique to characterize treated and untreated water and developed a system that can classify these two types of water. In order to classify the water types, four stages of processes are involved. There are process of collecting water samples, me...

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Main Author: Md Khayon, Jamaliza
Format: Thesis
Language:English
Published: 2009
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/68591/1/68591.pdf
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spelling my-uitm-ir.685912023-08-10T05:52:27Z Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon 2009 Md Khayon, Jamaliza Neural networks (Computer science) Microwaves. Including microwave circuits The main objective of this project is to introduce a technique to characterize treated and untreated water and developed a system that can classify these two types of water. In order to classify the water types, four stages of processes are involved. There are process of collecting water samples, measurement by using Microwave Non Destructive Testing method, finding parameter of dielectric constant and loss factor using FORTRAN software based on Sll parameters and classification process. The classification task is performed by using Artificial Neural Network (ANN) and the classification program was developed using MATLAB R2008a. The characteristic of the water samples was conducted using equipment known as Free Space Microwave Testing (FSMT) via the method of Microwave Non-Destructive Testing (NDT) at frequency 18GHz to 26GHz. Non-destructive testing is a method for determining the characteristics of materials without permanently changing its properties. There are 14 water samples was selected as a training samples for ANN .In order to see whether the developed system is successful or not another 28 samples have been tested. From the result obtained the ANN can classify all the testing samples correctly. 2009 Thesis https://ir.uitm.edu.my/id/eprint/68591/ https://ir.uitm.edu.my/id/eprint/68591/1/68591.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Saad, Hasnida
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Saad, Hasnida
topic Neural networks (Computer science)
Neural networks (Computer science)
spellingShingle Neural networks (Computer science)
Neural networks (Computer science)
Md Khayon, Jamaliza
Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
description The main objective of this project is to introduce a technique to characterize treated and untreated water and developed a system that can classify these two types of water. In order to classify the water types, four stages of processes are involved. There are process of collecting water samples, measurement by using Microwave Non Destructive Testing method, finding parameter of dielectric constant and loss factor using FORTRAN software based on Sll parameters and classification process. The classification task is performed by using Artificial Neural Network (ANN) and the classification program was developed using MATLAB R2008a. The characteristic of the water samples was conducted using equipment known as Free Space Microwave Testing (FSMT) via the method of Microwave Non-Destructive Testing (NDT) at frequency 18GHz to 26GHz. Non-destructive testing is a method for determining the characteristics of materials without permanently changing its properties. There are 14 water samples was selected as a training samples for ANN .In order to see whether the developed system is successful or not another 28 samples have been tested. From the result obtained the ANN can classify all the testing samples correctly.
format Thesis
qualification_level Bachelor degree
author Md Khayon, Jamaliza
author_facet Md Khayon, Jamaliza
author_sort Md Khayon, Jamaliza
title Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
title_short Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
title_full Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
title_fullStr Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
title_full_unstemmed Classification of treated and untreated water using artificial neural network (ANN) based on microwave non destructive testing (MNDT) method approach at 18-26GHz frequency range / Jamaliza Md Khayon
title_sort classification of treated and untreated water using artificial neural network (ann) based on microwave non destructive testing (mndt) method approach at 18-26ghz frequency range / jamaliza md khayon
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2009
url https://ir.uitm.edu.my/id/eprint/68591/1/68591.pdf
_version_ 1783735791654010880