Multi-layer perceptron model for air quality prediction
This study trained two MLP models with dierent activation functions in assessing the capability of the model for the prediction of air quality. The daily air quality data and meteorological variables from year 2010-2014 were assembled in training and testing the models. The MLP model with the combin...
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Universiti Putra Malaysia
2023
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| _version_ | 1833412565296742400 |
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| author | Abdullah S. Ismail M. Ahmed A.N. |
| author2 | 56509029800 |
| author_facet | 56509029800 Abdullah S. Ismail M. Ahmed A.N. |
| author_sort | Abdullah S. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This study trained two MLP models with dierent activation functions in assessing the capability of the model for the prediction of air quality. The daily air quality data and meteorological variables from year 2010-2014 were assembled in training and testing the models. The MLP model with the combination of tansig and purelin activation function revealed 69.0% of variance in data with 5.58 ?g/m3 (RMSE) and 80.0% of variance in data with 8.14 ?g/m3 (RMSE), during training and testing phase, respectively. This model is appropriate for operational used by respected authorities in managing air quality and as early warning during unhealthy level of air quality. � 2019, Universiti Putra Malaysia. |
| format | Article |
| id | my.uniten.dspace-24261 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Universiti Putra Malaysia |
| record_format | dspace |
| spelling | my.uniten.dspace-242612023-05-29T15:22:29Z Multi-layer perceptron model for air quality prediction Abdullah S. Ismail M. Ahmed A.N. 56509029800 57210403363 57214837520 This study trained two MLP models with dierent activation functions in assessing the capability of the model for the prediction of air quality. The daily air quality data and meteorological variables from year 2010-2014 were assembled in training and testing the models. The MLP model with the combination of tansig and purelin activation function revealed 69.0% of variance in data with 5.58 ?g/m3 (RMSE) and 80.0% of variance in data with 8.14 ?g/m3 (RMSE), during training and testing phase, respectively. This model is appropriate for operational used by respected authorities in managing air quality and as early warning during unhealthy level of air quality. � 2019, Universiti Putra Malaysia. Final 2023-05-29T07:22:29Z 2023-05-29T07:22:29Z 2019 Article 2-s2.0-85078661071 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078661071&partnerID=40&md5=32d4fa96a02de33e78449203a53b5e85 https://irepository.uniten.edu.my/handle/123456789/24261 13 S 85 95 Universiti Putra Malaysia Scopus |
| spellingShingle | Abdullah S. Ismail M. Ahmed A.N. Multi-layer perceptron model for air quality prediction |
| title | Multi-layer perceptron model for air quality prediction |
| title_full | Multi-layer perceptron model for air quality prediction |
| title_fullStr | Multi-layer perceptron model for air quality prediction |
| title_full_unstemmed | Multi-layer perceptron model for air quality prediction |
| title_short | Multi-layer perceptron model for air quality prediction |
| title_sort | multi-layer perceptron model for air quality prediction |
| url_provider | http://dspace.uniten.edu.my/ |