Intelligent classification of ammonia concentration based on odor profile

This thesis presents the intelligent classification of ammonia concentration based on the standard of oil and gas industries wastewater discharge. The intelligent classification using signal processing is a well-known technique in many applications and as well in the oil and gas industry. The intell...

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Main Author:	Muhamad Faruqi, Zahari
Format:	Thesis
Language:	English
Published:	2016
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/17671/16/Intelligent%20classification%20of%20ammonia%20concentration%20based%20on%20odor%20profile.pdf
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spelling	my-ump-ir.176712021-12-10T02:29:40Z Intelligent classification of ammonia concentration based on odor profile 2016-09 Muhamad Faruqi, Zahari TK Electrical engineering. Electronics Nuclear engineering This thesis presents the intelligent classification of ammonia concentration based on the standard of oil and gas industries wastewater discharge. The intelligent classification using signal processing is a well-known technique in many applications and as well in the oil and gas industry. The intelligent classification technique for ammonia concentration classification is a demanding technique especially in the environmental sector. Ammonia solution properties and ammonia solution preparations were studied in this thesis which commonly used in industry. The objectives of this thesis are to develop an intelligence classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule and to analyze performance of the intelligent classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule. In this thesis the ammonia odor profile has been pre-identified by chemist using four sensor array. The ammonia concentration was validated using a commercialized gas sensor and spectrophotometer to cross-validated e-nose instrument. The odor profile from two different samples; high (20 ppm and 25 ppm) and low (5 ppm, 10 ppm and 1 5ppm) concentration that have been normalized and visualized in a 2D plot to extract the unique patterns. The variance of the low and high concentration of ammonia odor profile has been identified as different group samples. This group samples have been analyzed statistically using Boxplot, calibration curve and proximity matrix, The thesis describes the statistical techniques to visualize the pattern and using mean features to classify between the low and high concentration. Two intelligent classification techniques have been used which are Artificial Neural Network (ANN) using the back-propagation approaches and then, the result of ANN model was cross-validated.using CBR. Both ANN model and CBR classifier have been measured using several performance measures. From the results, it is observed that ANN model and CBR classifier are capable of classifying 100% of ammonia concentration odor profile from the water. The results can also significantly reduce the cost and time, and improve product reliability and customer confidence. 2016-09 Thesis http://umpir.ump.edu.my/id/eprint/17671/ http://umpir.ump.edu.my/id/eprint/17671/16/Intelligent%20classification%20of%20ammonia%20concentration%20based%20on%20odor%20profile.pdf pdf en public masters Universiti Malaysia Pahang Faculty of Electrical and Electronics Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Muhamad Faruqi, Zahari Intelligent classification of ammonia concentration based on odor profile
description	This thesis presents the intelligent classification of ammonia concentration based on the standard of oil and gas industries wastewater discharge. The intelligent classification using signal processing is a well-known technique in many applications and as well in the oil and gas industry. The intelligent classification technique for ammonia concentration classification is a demanding technique especially in the environmental sector. Ammonia solution properties and ammonia solution preparations were studied in this thesis which commonly used in industry. The objectives of this thesis are to develop an intelligence classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule and to analyze performance of the intelligent classification of ammonia concentration based on the oil and gas industry wastewater discharge schedule. In this thesis the ammonia odor profile has been pre-identified by chemist using four sensor array. The ammonia concentration was validated using a commercialized gas sensor and spectrophotometer to cross-validated e-nose instrument. The odor profile from two different samples; high (20 ppm and 25 ppm) and low (5 ppm, 10 ppm and 1 5ppm) concentration that have been normalized and visualized in a 2D plot to extract the unique patterns. The variance of the low and high concentration of ammonia odor profile has been identified as different group samples. This group samples have been analyzed statistically using Boxplot, calibration curve and proximity matrix, The thesis describes the statistical techniques to visualize the pattern and using mean features to classify between the low and high concentration. Two intelligent classification techniques have been used which are Artificial Neural Network (ANN) using the back-propagation approaches and then, the result of ANN model was cross-validated.using CBR. Both ANN model and CBR classifier have been measured using several performance measures. From the results, it is observed that ANN model and CBR classifier are capable of classifying 100% of ammonia concentration odor profile from the water. The results can also significantly reduce the cost and time, and improve product reliability and customer confidence.
format	Thesis
qualification_level	Master's degree
author	Muhamad Faruqi, Zahari
author_facet	Muhamad Faruqi, Zahari
author_sort	Muhamad Faruqi, Zahari
title	Intelligent classification of ammonia concentration based on odor profile
title_short	Intelligent classification of ammonia concentration based on odor profile
title_full	Intelligent classification of ammonia concentration based on odor profile
title_fullStr	Intelligent classification of ammonia concentration based on odor profile
title_full_unstemmed	Intelligent classification of ammonia concentration based on odor profile
title_sort	intelligent classification of ammonia concentration based on odor profile
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Electrical and Electronics Engineering
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/17671/16/Intelligent%20classification%20of%20ammonia%20concentration%20based%20on%20odor%20profile.pdf
_version_	1783732022354640896

Intelligent classification of ammonia concentration based on odor profile

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