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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: Article
Language:English
Published: 2009
Subjects:
Microwave communication systems
Online Access:https://ir.uitm.edu.my/id/eprint/40399/1/40399.pdf
https://ir.uitm.edu.my/id/eprint/40399/
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spelling my.uitm.ir.403992023-08-15T02:14:58Z https://ir.uitm.edu.my/id/eprint/40399/ 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 Md Khayon, Jamaliza Microwave communication systems 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. 2009-05 Article NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/40399/1/40399.pdf 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) pp. 1-9.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Microwave communication systems
spellingShingle Microwave communication systems
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 Article
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
publishDate 2009
url https://ir.uitm.edu.my/id/eprint/40399/1/40399.pdf
https://ir.uitm.edu.my/id/eprint/40399/
_version_ 1775626310397198336
score 13.211869

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