Using Machine Learning for the Calibration of Airborne Particulate Sensors.
Sensors (Basel)
; 20(1)2019 Dec 23.
Article
em En
| MEDLINE
| ID: mdl-31877977
ABSTRACT
Airborne particulates are of particular significance for their human health impacts and their roles in both atmospheric radiative transfer and atmospheric chemistry. Observations of airborne particulates are typically made by environmental agencies using rather expensive instruments. Due to the expense of the instruments usually used by environment agencies, the number of sensors that can be deployed is limited. In this study we show that machine learning can be used to effectively calibrate lower cost optical particle counters. For this calibration it is critical that measurements of the atmospheric pressure, humidity, and temperature are also made.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos