Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants
The project explores the use of machine learning approach to develop a model to predict the next day air quality based on the concentration of sulfur dioxide(SO2) and particulate matter(PM10) in the previous few days. The data source is the Hong Kong government environmental protection department (E...
| Hovedforfatter: | |
|---|---|
| Andre forfattere: | |
| Format: | Final Year Project (FYP) |
| Sprog: | English |
| Udgivet: |
Nanyang Technological University
2021
|
| Fag: | |
| Online adgang: | https://hdl.handle.net/10356/154128 |
| _version_ | 1826122843209859072 |
|---|---|
| author | Nisar Nur Nasreen |
| author2 | Wong Kin Shun, Terence |
| author_facet | Wong Kin Shun, Terence Nisar Nur Nasreen |
| author_sort | Nisar Nur Nasreen |
| collection | NTU |
| description | The project explores the use of machine learning approach to develop a model to predict the next day air quality based on the concentration of sulfur dioxide(SO2) and particulate matter(PM10) in the previous few days. The data source is the Hong Kong government environmental protection department (EPD) website. The data from the EPD is used to train a machine learning model to recognise the days with high pollutant levels. After training, the machine learning model will be tested by making forecasts using the new measured pollutant data. The sci-kit learn module was used. |
| first_indexed | 2024-10-01T05:54:49Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/154128 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:54:49Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1541282023-07-07T18:37:31Z Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants Nisar Nur Nasreen Wong Kin Shun, Terence School of Electrical and Electronic Engineering EKSWONG@ntu.edu.sg Engineering::Electrical and electronic engineering The project explores the use of machine learning approach to develop a model to predict the next day air quality based on the concentration of sulfur dioxide(SO2) and particulate matter(PM10) in the previous few days. The data source is the Hong Kong government environmental protection department (EPD) website. The data from the EPD is used to train a machine learning model to recognise the days with high pollutant levels. After training, the machine learning model will be tested by making forecasts using the new measured pollutant data. The sci-kit learn module was used. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-12-19T10:53:51Z 2021-12-19T10:53:51Z 2021 Final Year Project (FYP) Nisar Nur Nasreen (2021). Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154128 https://hdl.handle.net/10356/154128 en A2410-202 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Nisar Nur Nasreen Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title | Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title_full | Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title_fullStr | Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title_full_unstemmed | Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title_short | Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants |
| title_sort | data driven air pollution forecast for so2 and pm10 atmospheric pollutants |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/154128 |
| work_keys_str_mv | AT nisarnurnasreen datadrivenairpollutionforecastforso2andpm10atmosphericpollutants |