AIMC Topic: Seoul

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Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.

Environmental pollution (Barking, Essex : 1987) Sep 6, 2016
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...
Neural Networks, Computer Forecasting Republic of Korea Temperature Wind China Models, Theoretical Environmental Monitoring Particle Size Air Pollutants Particulate Matter Seasons Meteorology Seoul
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Machine learning-based prediction of ambient CO and CH concentrations with high temporal resolution in Seoul metropolitan area.

Environmental pollution (Barking, Essex : 1987) Jul 1, 2025
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Machine Learning Republic of Korea Environmental Monitoring Air Pollutants Air Pollution Methane Carbon Dioxide Greenhouse Gases Seoul
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