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regression-imputation
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A novel regression imputation framework for Tehran air pollution monitoring network using outputs from WRF and CAMx models
, Article Atmospheric Environment ; Volume 187 , 2018 , Pages 24-33 ; 13522310 (ISSN) ; Karimi, S ; Hosseini, V ; Yazgi, D ; Torbatian, S ; Sharif University of Technology
Elsevier Ltd
2018
Abstract
Missing or incomplete data in short or long intervals is a common problem in measuring air pollution. Severe issues may arise when dealing with missing data for time-series prediction schemes or mean analysis. This study aimed to develop a new regression imputation framework to impute missing values in the hourly air quality data set of Tehran and enhance the applicability of Tehran Air Pollution Forecasting System (TAPFS). The proposed framework was designed based on three types of features including measurements of other stations, WRF and CAMx physical models. In this framework, elastic net and neuro-fuzzy networks were efficiently combined in a two-layer structure. The framework was...