Single interpolation: A review of application in air quality data sets
Abstract
The Single imputation methods have been wide-used techniques
among researchers in the field of missing data in
environmental data sets. Usually, ignorable the missing data
and discard those incomplete cases in data sets as approach.
However, this is not suitable for time-series prediction
especially for air quality data sets. From the literatures study,
has a valid method to predict the missing data in air pollutant
data sets, its interpolation method. Interpolation as a well
known problem in numerical method and it has been used in
difference approaches in environmental data sets. The purpose
of this paper is to present an overview of the existing literature
about single interpolation techniques assessment to predict
missing data in data air pollutant sets.
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