Digital Twin-Based Framework for Real-Time Monitoring and Analysis of Urban Mobile-Source Emissions

This study introduces a digital twin paradigm that uses both stationary and mobile sensors and cutting-edge machine learning for urban air quality monitoring. By boosting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics&g...

詳細記述

書誌詳細

出版年:	Atmosphere
主要な著者:	Peter Zhivkov, Stefka Fidanova, Ivan Dimov
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-06-01
主題:	digital twins machine learning calibration urban air pollution graph neural networks (GNNs)
オンライン･アクセス:	https://www.mdpi.com/2073-4433/16/6/731