Retrieval of aerosol size distribution using improved quantum-behaved particle swarm optimization on spectral extinction measurements

An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm,...

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Bibliographic Details
Published in:Particuology 2016-10, Vol.28 (5), p.6-14
Main Authors: He, Zhenzong, Qi, Hong, Chen, Qin, Ruan, Liming
Format: Article
Language:English
Subjects:
Aerosol
Aerosol size distribution
Inverse problem
Quantum-behaved particle swarm optimization
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Summary:An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization param- eters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and S0 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQpSO algorithm is an effective and reliable technique for estimatinz ASD.
ISSN:1674-2001
2210-4291
DOI:10.1016/j.partic.2014.12.016