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IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT

Wastewater treatment plants play an important role in maintaining water quality and preserving the environment. The problem addressed in this study is the inefficiency of controller of the activate sludge process due to high energy consumption of the activated sludge process, lack of adaptability of...

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Main Author: Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya
Format: Final Year Project Report
Language:English
English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2023
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/43164/1/Ilayka%20Iziahwati%2024pgs.pdf
http://ir.unimas.my/id/eprint/43164/2/Ilayka%20Iziahwati%20ft.pdf
http://ir.unimas.my/id/eprint/43164/
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spelling my.unimas.ir.431642023-10-19T07:47:24Z http://ir.unimas.my/id/eprint/43164/ IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya T Technology (General) Wastewater treatment plants play an important role in maintaining water quality and preserving the environment. The problem addressed in this study is the inefficiency of controller of the activate sludge process due to high energy consumption of the activated sludge process, lack of adaptability of the default controller, and strict effluent quality compliance set by local and national authorities. The objectives of this research are to develop an effective control strategy for the activated sludge process in tank 5 and to enhance the overall performance of the wastewater treatment plant. The proposed method of research utilizes a fuzzy neural network to model and optimize the control parameter of tank 5 which is the oxygen transfer coefficient. The proposed control strategy combines the benefits of fuzzy logic and neural network techniques to provide robust and adaptive control in complex and uncertain wastewater treatment systems. The modelling of the proposed controller is by employing the data of default controller. The outcomes of this study are expected to include improved process efficiency, enhanced treatment quality, reduced operational costs, and minimized environmental impact. The results will provide valuable insights for the wastewater treatment plant operators and contribute to the advancement of control strategies in wastewater treatment systems. Universiti Malaysia Sarawak, (UNIMAS) 2023 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/43164/1/Ilayka%20Iziahwati%2024pgs.pdf text en http://ir.unimas.my/id/eprint/43164/2/Ilayka%20Iziahwati%20ft.pdf Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya (2023) IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT. [Final Year Project Report] (Unpublished)
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya
IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
description Wastewater treatment plants play an important role in maintaining water quality and preserving the environment. The problem addressed in this study is the inefficiency of controller of the activate sludge process due to high energy consumption of the activated sludge process, lack of adaptability of the default controller, and strict effluent quality compliance set by local and national authorities. The objectives of this research are to develop an effective control strategy for the activated sludge process in tank 5 and to enhance the overall performance of the wastewater treatment plant. The proposed method of research utilizes a fuzzy neural network to model and optimize the control parameter of tank 5 which is the oxygen transfer coefficient. The proposed control strategy combines the benefits of fuzzy logic and neural network techniques to provide robust and adaptive control in complex and uncertain wastewater treatment systems. The modelling of the proposed controller is by employing the data of default controller. The outcomes of this study are expected to include improved process efficiency, enhanced treatment quality, reduced operational costs, and minimized environmental impact. The results will provide valuable insights for the wastewater treatment plant operators and contribute to the advancement of control strategies in wastewater treatment systems.
format Final Year Project Report
author Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya
author_facet Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya
author_sort Ilayka Iziahwati, Mohd Jaya @ Mohd Yahya
title IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
title_short IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
title_full IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
title_fullStr IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
title_full_unstemmed IMPLEMENTATION OF FUZZY NEURAL NETWORK IN ACTIVATED SLUDGE PROCESS OF THE WASTEWATER TREATMENT PLANT
title_sort implementation of fuzzy neural network in activated sludge process of the wastewater treatment plant
publisher Universiti Malaysia Sarawak, (UNIMAS)
publishDate 2023
url http://ir.unimas.my/id/eprint/43164/1/Ilayka%20Iziahwati%2024pgs.pdf
http://ir.unimas.my/id/eprint/43164/2/Ilayka%20Iziahwati%20ft.pdf
http://ir.unimas.my/id/eprint/43164/
_version_ 1781710361793134592
score 13.211869

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