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

作     者：Zhenzong He Hong Qi Qin Chen Liming Ruan 

作者机构：School of Energy Science and Engineering Harbin Institute of Technology 92 West Dazhi Street Harbin 150001 China 

出 版 物：《Particuology》 (颗粒学报（英文版）)

年 卷 期：2016年第14卷第5期

页      面：6-14页

核心收录：

学科分类：07[理学] 

基　　金：Support from the National Natural Science Foundation of China (No. 51476043)  the Major National Scientific Instruments and Equipment Development Special Foundation of China (No. 51327803) and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 51421063) is gratefully acknowledged 

主　　题：Quantum behaved particle swarmoptimization AerosolAerosol size distribution Inverse problem 

摘      要：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.