A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset
It is understood that water is the most valuable natural resource and as like wastewater treatment plants are necessary base to control the environmental balance where they are installed. To ensure good quality effluents, the dynamic and complicated wastewater treatment procedure must be handled eff...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE Explorer
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/35203/ http://umpir.ump.edu.my/id/eprint/35203/1/A_Supervised_Neural_Network-based_predictive_model_for_petrochemical_wastewater_treatment_dataset.pdf |
| _version_ | 1848824716374048768 |
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| author | Varun, Geetha Mohan Mubarak Ali, Al-Fahim Vijayan, Bincy Lathakumary Saiful, Azad Mohamed Ariff, Ameedeen |
| author_facet | Varun, Geetha Mohan Mubarak Ali, Al-Fahim Vijayan, Bincy Lathakumary Saiful, Azad Mohamed Ariff, Ameedeen |
| author_sort | Varun, Geetha Mohan |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | It is understood that water is the most valuable natural resource and as like wastewater treatment plants are necessary base to control the environmental balance where they are installed. To ensure good quality effluents, the dynamic and complicated wastewater treatment procedure must be handled efficiently. A global interest has been prompted in conservation, reuse, and alternative water sources due to growing treats over water supply scarcity. Water utilities are searching for more efficient ways to maintain their resources globally. The development of machine learning techniques is starting to offer real opportunities to operate water treatment systems in more efficient manners. This paperwork shows research as well as its development work implemented to predict the performance of petrochemical wastewater treatment. The data were used from a reputed chemical plant and the predictive models were developed by implementation of Backpropagation Neural Network using sample datasets with the parameters of wastewater dataset. |
| first_indexed | 2025-11-15T03:17:27Z |
| format | Conference or Workshop Item |
| id | ump-35203 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:17:27Z |
| publishDate | 2022 |
| publisher | IEEE Explorer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-352032022-09-14T06:54:04Z http://umpir.ump.edu.my/id/eprint/35203/ A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset Varun, Geetha Mohan Mubarak Ali, Al-Fahim Vijayan, Bincy Lathakumary Saiful, Azad Mohamed Ariff, Ameedeen TP Chemical technology TS Manufactures It is understood that water is the most valuable natural resource and as like wastewater treatment plants are necessary base to control the environmental balance where they are installed. To ensure good quality effluents, the dynamic and complicated wastewater treatment procedure must be handled efficiently. A global interest has been prompted in conservation, reuse, and alternative water sources due to growing treats over water supply scarcity. Water utilities are searching for more efficient ways to maintain their resources globally. The development of machine learning techniques is starting to offer real opportunities to operate water treatment systems in more efficient manners. This paperwork shows research as well as its development work implemented to predict the performance of petrochemical wastewater treatment. The data were used from a reputed chemical plant and the predictive models were developed by implementation of Backpropagation Neural Network using sample datasets with the parameters of wastewater dataset. IEEE Explorer 2022-05-10 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/35203/1/A_Supervised_Neural_Network-based_predictive_model_for_petrochemical_wastewater_treatment_dataset.pdf Varun, Geetha Mohan and Mubarak Ali, Al-Fahim and Vijayan, Bincy Lathakumary and Saiful, Azad and Mohamed Ariff, Ameedeen (2022) A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset. In: 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) , 16-18 February 2022 , Trichy, India. pp. 1-5.. ISBN 978-1-6654-3648-9 (Online); 978-1-6654-3647-2(PoD) (Published) http://10.1109/ICEEICT53079.2022.9768566 http://10.1109/ICEEICT53079.2022.9768566 |
| spellingShingle | TP Chemical technology TS Manufactures Varun, Geetha Mohan Mubarak Ali, Al-Fahim Vijayan, Bincy Lathakumary Saiful, Azad Mohamed Ariff, Ameedeen A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title | A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title_full | A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title_fullStr | A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title_full_unstemmed | A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title_short | A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset |
| title_sort | supervised neural network-based predictive model for petrochemical wastewater treatment dataset |
| topic | TP Chemical technology TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/35203/ http://umpir.ump.edu.my/id/eprint/35203/ http://umpir.ump.edu.my/id/eprint/35203/ http://umpir.ump.edu.my/id/eprint/35203/1/A_Supervised_Neural_Network-based_predictive_model_for_petrochemical_wastewater_treatment_dataset.pdf |