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Imputation methods for filling missing data in urban air pollution data for Malaysia

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Main Authors: Nur Afiqah, Zakaria, Norazian, Mohamed Noor
Other Authors: nurafiqahzakaria15@gmail.com
Format: Article
Language:English
Published: NR&DI URBAN-INCERC 2020
Subjects:
Air pollution
Missing data
Imputation methods
Multiple imputation
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/68510
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id my.unimap-68510
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spelling my.unimap-685102020-10-26T04:58:19Z Imputation methods for filling missing data in urban air pollution data for Malaysia Nur Afiqah, Zakaria Norazian, Mohamed Noor nurafiqahzakaria15@gmail.com norazian@unimap.edu.my Air pollution Missing data Imputation methods Multiple imputation Link to publisher's homepage at https://uac.incd.ro/EN/index.htm The air quality measurement data obtained from the continuous ambient air quality monitoring (CAAQM) station usually contained missing data. The missing observations of the data usually occurred due to machine failure, routine maintenance and human error. In this study, the hourly monitoring data of CO, O3, PM10, SO2, NOx, NO2, ambient temperature and humidity were used to evaluate four imputation methods (Mean Top Bottom, Linear Regression, Multiple Imputation and Nearest Neighbour). The air pollutants observations were simulated into four percentages of simulated missing data i.e. 5%, 10%, 15% and 20%. Performance measures namely the Mean Absolute Error, Root Mean Squared Error, Coefficient of Determination and Index of Agreement were used to describe the goodness of fit of the imputation methods. From the results of the performance measures, Mean Top Bottom method was selected as the most appropriate imputation method for filling in the missing values in air pollutants data. 2020-10-26T04:58:19Z 2020-10-26T04:58:19Z 2018 Article Urbanism. Arhitectură. Construcţii, vol.9(2), 2018, pages 169-166. http://dspace.unimap.edu.my:80/xmlui/handle/123456789/68510 2069-0509 (print) 2069-6469 (online) https://uac.incd.ro/EN/index.htm en NR&DI URBAN-INCERC
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Air pollution
Missing data
Imputation methods
Multiple imputation
spellingShingle Air pollution
Missing data
Imputation methods
Multiple imputation
Nur Afiqah, Zakaria
Norazian, Mohamed Noor
Imputation methods for filling missing data in urban air pollution data for Malaysia
description Link to publisher's homepage at https://uac.incd.ro/EN/index.htm
author2 nurafiqahzakaria15@gmail.com
author_facet nurafiqahzakaria15@gmail.com
Nur Afiqah, Zakaria
Norazian, Mohamed Noor
format Article
author Nur Afiqah, Zakaria
Norazian, Mohamed Noor
author_sort Nur Afiqah, Zakaria
title Imputation methods for filling missing data in urban air pollution data for Malaysia
title_short Imputation methods for filling missing data in urban air pollution data for Malaysia
title_full Imputation methods for filling missing data in urban air pollution data for Malaysia
title_fullStr Imputation methods for filling missing data in urban air pollution data for Malaysia
title_full_unstemmed Imputation methods for filling missing data in urban air pollution data for Malaysia
title_sort imputation methods for filling missing data in urban air pollution data for malaysia
publisher NR&DI URBAN-INCERC
publishDate 2020
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/68510
_version_ 1698698470619086848
score 13.222552

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