Clustering Imputation for Air Pollution Data

Alahamade, Wedad, Lake, Iain, Reeves, Claire E. and De La Iglesia, Beatriz (2020) Clustering Imputation for Air Pollution Data. In: Hybrid Artificial Intelligent Systems. Springer International Publishing AG, Cham, pp. 585-597. ISBN 978-3-030-61705-9

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Abstract

Air pollution is a global problem. The assessment of air pollution concentration data is important for evaluating human exposure and the associated risk to health. Unfortunately, air pollution monitoring stations often have periods of missing data or do not measure all pollutants. In this study, we experiment with different approaches to estimate the whole time series for a missing pollutant at a monitoring station as well as missing values within a time series. The main goal is to reduce the uncertainty in air quality assessment.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
Faculty of Science > School of Environmental Sciences
Faculty of Science > Tyndall Centre for Climatic Change
Depositing User: LivePure Connector
Date Deposited: 12 Nov 2020 01:22
Last Modified: 16 Jan 2021 00:33
URI: https://ueaeprints.uea.ac.uk/id/eprint/77669
DOI: 10.1007/978-3-030-61705-9_48

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