Inversion algorithm of black carbon mixing state based on machine learning

The radiative properties of black carbon (BC) are significantly influenced by its mixing state. The single-particle soot photometer (SP2) is a widely recognized instrument for quantifying BC mixing state. However, the derivation of BC mixing state from SP2 is quite challenging. Since the SP2 records...

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Vydané v:	Atmospheric measurement techniques Ročník 18; číslo 5; s. 1149 - 1162
Hlavní autori:	Tian, Zeyuan, Wang, Jiandong, Wang, Jiaping, Liu, Chao, Xing, Jia, Wang, Jinbo, Zhang, Zhouyang, Jin, Yuzhi, Shen, Sunan, Wang, Bin, Nie, Wei, Huang, Xin, Ding, Aijun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Katlenburg-Lindau Copernicus GmbH 06.03.2025 Copernicus Publications
Predmet:	Aerosols Algorithms Analysis Black carbon Carbon Data analysis Data mining Data processing Decision making Ensemble learning Lasers Leading edges Learning algorithms Light Machine learning Optical properties Particle size Photometers Physical properties Protective coatings Radiation Real time Sensors Signal to noise ratio
ISSN:	1867-8548, 1867-1381, 1867-8548
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