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Determination of aerosol particle size distribution by a novel artificial bee colony-differential evolution hybrid algorithm

He Zhen-Zong (Nanjing University of Aeronautics and Astronautics (NUAA), College of Energy and Power Engineering, Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing, P.R. China)
Mao Jun-Kui (Nanjing University of Aeronautics and Astronautics (NUAA), College of Energy and Power Engineering, Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing, P.R. China)
Han Xing-Si (Nanjing University of Aeronautics and Astronautics (NUAA), College of Energy and Power Engineering, Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing, P.R. China)
Liu Zhao-Ying (Nanjing University of Aeronautics and Astronautics (NUAA), College of Energy and Power Engineering, Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing, P.R. China)

The aerosol size distribution, a vitally important environmental quality evaluation criterion, has a significant influence on radiative transfer and meteorological phenomena. To measure the aerosol size distribution effectively and accurately, the light scattering measurement method combined with a novel artificial bee colony-differential evolution hybrid algorithm which was based on the artificial bee colony algorithm and differential evolution algorithm, was proposed. First, the retrieval accuracy and convergence properties of the artificial bee colony-differential evolution algorithm were compared with those of the artificial bee colony algorithm. The results revealed that the artificial bee colony-differential evolution algorithm could avoid the phenomenon of local optima and low convergence accuracy which exited in artificial bee colony algorithm. Then, the parametric estimation of two commonly used mono modal aerosol size distribution, i.e. the Gamma distribution and the logarithmic normal distribution were studied under different random measurement errors. The investigation indicated that the retrieval results using the artificial bee colony-differential evolution showed better accuracy and robustness than those using the artificial bee colony. Moreover, the retrieval parameters with better monodromy characteristic would have better inverse accuracy. Finally, the actual measured aerosol size distribution over city of Harbin, China were also retrieved. All the results confirm that the artificial bee colony-differential evolution algorithm was an effective and reliable technique for estimating the aerosol size distribution.

Keywords: artificial bee colony algorithm, aerosol size distribution, inverse problem, light scattering measurement method