Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 11, issue 11
Articles | Volume 11, issue 11
https://doi.org/10.5194/amt-11-6259-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-6259-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 11
Research article
 | 
20 Nov 2018
Research article |  | 20 Nov 2018

Improved real-time bio-aerosol classification using artificial neural networks

Maciej Leśkiewicz, Miron Kaliszewski, Maksymilian Włodarski, Jarosław Młyńczak, Zygmunt Mierczyk, and Krzysztof Kopczyński

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Short summary
In this study we demonstrate the application of artificial neural networks to the real-time analysis of single-particle fluorescence fingerprints acquired using BARDet (a BioAeRosol Detector). 48 different aerosols including pollens, bacteria, fungi, spores and nonbiological substances were characterized. An entirely new approach to data analysis using a decision tree comprising 22 independent neural networks was discussed. A very high accuracy of aerosol classification in real time resulted.
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