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• W17921641 abstract "Air pollution has a direct impact to human health, and data-driven air quality models are useful for evaluating population exposure to air pollutants. In this paper, we propose a novel region-based Gaussian process model for estimating urban air pollution dispersion, and applied it to a large dataset of ultrafine particle (UFP) measurements collected from a network of sensors located on several trams in the city of Zurich. We show that compared to existing grid-based models, the region-based model produces better predictions across aggregates of all time scales. The new model is appropriate for many useful user applications such as exposure assessment and anomaly detection." @default.
• W17921641 created "2016-06-24" @default.
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• W17921641 date "2014-06-20" @default.
• W17921641 modified "2023-10-01" @default.
• W17921641 title "A Region-Based Model for Estimating Urban Air Pollution" @default.
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• W17921641 doi "https://doi.org/10.1609/aaai.v28i1.8768" @default.
• W17921641 hasPublicationYear "2014" @default.
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