Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154128
Title: Data driven air pollution forecast for SO2 and PM10 atmospheric pollutants
Authors: Nisar Nur Nasreen
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: 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
Project: A2410-202
Abstract: 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.
URI: https://hdl.handle.net/10356/154128
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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