Concept Drift Mitigation in Low-Cost Air Quality Monitoring Networks

Future air quality monitoring networks will include fleets of low-cost gas and particulate matter sensors calibrated using machine learning techniques. Unfortunately, it is well known that concept drift is one of the primary causes of losses in data quality in operational scenarios. This work focuse...

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Bibliografiske detaljer

Principais autores:	Gerardo D’Elia, Matteo Ferro, Paolo Sommella, Sergio Ferlito, Saverio De Vito, Girolamo Di Francia
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-03-01
Serier:	Proceedings
Fag:	air quality network concept drift general calibration relative expanded uncertainty
Online adgang:	https://www.mdpi.com/2504-3900/97/1/2
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