Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater

The rise in wastewater as a source of pollution rank equal to climate change as the most urgent environmental issues currently. The rapidly growing industrialization and urbanization, improper sanitary disposal and household wastewater has contributed to this pollution. Such concerns pose potential...

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Main Authors: Olanrewaju, Rashidah Funke, Rehab, Mariam, Ahmed, Abdulkadir Adekunle
Format: Proceeding Paper
Language:English
English
Published: 10.1109/ICSIMA.2017.8311989 2018
Subjects:
Online Access:http://irep.iium.edu.my/61395/
http://irep.iium.edu.my/61395/1/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_complete.pdf
http://irep.iium.edu.my/61395/2/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_scopus.pdf
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author Olanrewaju, Rashidah Funke
Rehab, Mariam
Ahmed, Abdulkadir Adekunle
author_facet Olanrewaju, Rashidah Funke
Rehab, Mariam
Ahmed, Abdulkadir Adekunle
author_sort Olanrewaju, Rashidah Funke
building IIUM Repository
collection Online Access
description The rise in wastewater as a source of pollution rank equal to climate change as the most urgent environmental issues currently. The rapidly growing industrialization and urbanization, improper sanitary disposal and household wastewater has contributed to this pollution. Such concerns pose potential risks and hazards towards the public health and animal ecosystems. Meanwhile, the wastewater treatment process involves both physical and chemical process chain which is susceptible to error due to the human factor, variation in the quality of raw water as well as chemical/physical characteristics of such raw materials used. An intelligent method for predicting the optimal adsorption capacity for removal of pollutants in wastewater based on ANN is proposed to reduce the percentage error and obtain optimal treatment efficiency. The primary focus is to identify the operating parameters which affect adsorption capacity. Using the parameters as input factors, the proposed system is trained and tested to obtain an optimal adsorption capacity to remove pollutants. Evaluation and validation of the proposed method on real data depend on the mean absolute error (MAE), mean square error (MSE), root mean square error(RMSE), normalized mean square error(NMSE) and correlation of efficiency. The correlation between the experimental and ANN result is 0.99881 of 1.00000 which indicates that ANN is a perfect match.
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format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T16:56:45Z
publishDate 2018
publisher 10.1109/ICSIMA.2017.8311989
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spelling iium-613952018-11-01T06:41:21Z http://irep.iium.edu.my/61395/ Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater Olanrewaju, Rashidah Funke Rehab, Mariam Ahmed, Abdulkadir Adekunle TD Environmental technology. Sanitary engineering TD895 Industrial sanitation. Industrial wastes The rise in wastewater as a source of pollution rank equal to climate change as the most urgent environmental issues currently. The rapidly growing industrialization and urbanization, improper sanitary disposal and household wastewater has contributed to this pollution. Such concerns pose potential risks and hazards towards the public health and animal ecosystems. Meanwhile, the wastewater treatment process involves both physical and chemical process chain which is susceptible to error due to the human factor, variation in the quality of raw water as well as chemical/physical characteristics of such raw materials used. An intelligent method for predicting the optimal adsorption capacity for removal of pollutants in wastewater based on ANN is proposed to reduce the percentage error and obtain optimal treatment efficiency. The primary focus is to identify the operating parameters which affect adsorption capacity. Using the parameters as input factors, the proposed system is trained and tested to obtain an optimal adsorption capacity to remove pollutants. Evaluation and validation of the proposed method on real data depend on the mean absolute error (MAE), mean square error (MSE), root mean square error(RMSE), normalized mean square error(NMSE) and correlation of efficiency. The correlation between the experimental and ANN result is 0.99881 of 1.00000 which indicates that ANN is a perfect match. 10.1109/ICSIMA.2017.8311989 2018-03-09 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/61395/1/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_complete.pdf application/pdf en http://irep.iium.edu.my/61395/2/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_scopus.pdf Olanrewaju, Rashidah Funke and Rehab, Mariam and Ahmed, Abdulkadir Adekunle (2018) Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater. In: 4th IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) 2017, 28th-30th November 2017, Putrajaya. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8311989 10.1109/ICSIMA.2017.8311989
spellingShingle TD Environmental technology. Sanitary engineering
TD895 Industrial sanitation. Industrial wastes
Olanrewaju, Rashidah Funke
Rehab, Mariam
Ahmed, Abdulkadir Adekunle
Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title_full Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title_fullStr Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title_full_unstemmed Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title_short Modeling of ANN to determine optimum adsorption capacity for removal of pollutants in wastewater
title_sort modeling of ann to determine optimum adsorption capacity for removal of pollutants in wastewater
topic TD Environmental technology. Sanitary engineering
TD895 Industrial sanitation. Industrial wastes
url http://irep.iium.edu.my/61395/
http://irep.iium.edu.my/61395/
http://irep.iium.edu.my/61395/
http://irep.iium.edu.my/61395/1/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_complete.pdf
http://irep.iium.edu.my/61395/2/61395_Modeling%20of%20ANN%20to%20determine%20optimum%20adsorption_scopus.pdf