Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment
The important process in wastewater treatment is the removal of pollutants, and the dataset having so many features may cause difficulty training the data and predicting key variables. This work aims to propose set parameters through normalization techniques, feature selection techniques, and AI tec...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2022
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/35990/2/Predictive%20Models%20Using%20Supervised%20Neural_FULL.pdf http://umpir.ump.edu.my/id/eprint/35990/3/Predictive%20models%20using%20supervised%20neural%20network%20for%20pollutant%20removal%20.pdf |
| _version_ | 1825814697643868160 |
|---|---|
| author | Mohan, Varun Geetha Al-Fahim, Mubarak-Ali Ameedeen, Mohamed Ariff Vijayan, Bincy Lathakumary Aminuddin, Afrig Widayani, Wiwi |
| author_facet | Mohan, Varun Geetha Al-Fahim, Mubarak-Ali Ameedeen, Mohamed Ariff Vijayan, Bincy Lathakumary Aminuddin, Afrig Widayani, Wiwi |
| author_sort | Mohan, Varun Geetha |
| collection | UMP |
| description | The important process in wastewater treatment is the removal of pollutants, and the dataset having so many features may cause difficulty training the data and predicting key variables. This work aims to propose set parameters through normalization techniques, feature selection techniques, and AI techniques. The datasets have 36 features and a key parameter, and experimental datasets contain 628. Constant factor, Z-score, and Min-max normalization are the normalization techniques used to normalize the petrochemical wastewater dataset. SelectKBest, ExtraTreeClassifier, PCA, and RFE are the feature selection techniques for data mining. Then finally done with AI implementation with the help of a supervised neural network technique called backpropagation neural network (BPNN). |
| first_indexed | 2024-03-06T13:02:24Z |
| format | Conference or Workshop Item |
| id | UMPir35990 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T13:02:24Z |
| publishDate | 2022 |
| publisher | IEEE |
| record_format | dspace |
| spelling | UMPir359902022-12-21T01:56:37Z http://umpir.ump.edu.my/id/eprint/35990/ Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment Mohan, Varun Geetha Al-Fahim, Mubarak-Ali Ameedeen, Mohamed Ariff Vijayan, Bincy Lathakumary Aminuddin, Afrig Widayani, Wiwi QA76 Computer software QD Chemistry TA Engineering (General). Civil engineering (General) TP Chemical technology The important process in wastewater treatment is the removal of pollutants, and the dataset having so many features may cause difficulty training the data and predicting key variables. This work aims to propose set parameters through normalization techniques, feature selection techniques, and AI techniques. The datasets have 36 features and a key parameter, and experimental datasets contain 628. Constant factor, Z-score, and Min-max normalization are the normalization techniques used to normalize the petrochemical wastewater dataset. SelectKBest, ExtraTreeClassifier, PCA, and RFE are the feature selection techniques for data mining. Then finally done with AI implementation with the help of a supervised neural network technique called backpropagation neural network (BPNN). IEEE 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/35990/2/Predictive%20Models%20Using%20Supervised%20Neural_FULL.pdf pdf en http://umpir.ump.edu.my/id/eprint/35990/3/Predictive%20models%20using%20supervised%20neural%20network%20for%20pollutant%20removal%20.pdf Mohan, Varun Geetha and Al-Fahim, Mubarak-Ali and Ameedeen, Mohamed Ariff and Vijayan, Bincy Lathakumary and Aminuddin, Afrig and Widayani, Wiwi (2022) Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment. In: 2022 5th International Conference on Information and Communications Technology (ICOIACT) , 24-25 August 2022 , Yogyakarta, Indonesia. pp. 1-6.. ISSN 2770-4661 ISBN 978-1-6654-5140-6 (Published) https://doi.org/ 10.1109/ICOIACT55506.2022.9971929 |
| spellingShingle | QA76 Computer software QD Chemistry TA Engineering (General). Civil engineering (General) TP Chemical technology Mohan, Varun Geetha Al-Fahim, Mubarak-Ali Ameedeen, Mohamed Ariff Vijayan, Bincy Lathakumary Aminuddin, Afrig Widayani, Wiwi Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title | Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title_full | Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title_fullStr | Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title_full_unstemmed | Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title_short | Predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| title_sort | predictive models using supervised neural network for pollutant removal efficiency in petrochemical wastewater treatment |
| topic | QA76 Computer software QD Chemistry TA Engineering (General). Civil engineering (General) TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/35990/2/Predictive%20Models%20Using%20Supervised%20Neural_FULL.pdf http://umpir.ump.edu.my/id/eprint/35990/3/Predictive%20models%20using%20supervised%20neural%20network%20for%20pollutant%20removal%20.pdf |
| work_keys_str_mv | AT mohanvarungeetha predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment AT alfahimmubarakali predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment AT ameedeenmohamedariff predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment AT vijayanbincylathakumary predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment AT aminuddinafrig predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment AT widayaniwiwi predictivemodelsusingsupervisedneuralnetworkforpollutantremovalefficiencyinpetrochemicalwastewatertreatment |