Deep Smooth Random Sampling and Association Attention for Air Quality Anomaly Detection

Deep Smooth Random Sampling and Association Attention for Air Quality Anomaly Detection

Real-time monitoring and timely warning of air quality are vital components of building livable cities and implementing the “Healthy China” strategy. Real-time, efficient, and accurate detection of air quality anomalies holds great significance. However, almost all existing methods for air quality a...

Bibliografiset tiedot
Päätekijät:	Peng Wang, Minhang Li, Xiaoying Zhi, Xiliang Liu, Zhixiang He, Ziyue Di, Xiang Zhu, Yanchen Zhu, Wenqiong Cui, Wenyu Deng, Wenhan Fan
Aineistotyyppi:	Artikkeli
Kieli:	English
Julkaistu:	MDPI AG 2024-06-01
Sarja:	Mathematics
Aiheet:	air quality anomaly detection imbalanced data processing geographical third law transformer livable cities
Linkit:	https://www.mdpi.com/2227-7390/12/13/2048

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