期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2020
卷号：616
期号：1
DOI：10.1088/1755-1315/616/1/012002
语种：English
出版社：IOP Publishing
摘要：Imputation plays an essential role in handling the issue of missing data. The conventional techniques applied to overcome this problem are single imputation (SI) and multiple imputations (MI). These statistical strategies have their strengths and limitations in replacing missing data. This article reviews the state of the art of imputation methods employed in general publications in replacing missing values for air pollution data. A comprehensive review of the literature identifies the use of SI and MI slightly increases over the year. This paper concludes on the trend and the approaches used in the imputation methods. Subsequently, this paper put forward the gaps in imputation technique that less utilized a machine-learning approach in providing a substitute for missing values in air pollution data. The future direction of the research is to extend more machine-learning approach with higher accuracy with higher performance in imputing missing values.
