摘要
The ant colony optimization （ACO） algorithm based on the probability density function is applied for the retrieval of spherical particle size distribution （PSD）. The spectral extinction data based on the Mie theory and the Lambert-Beer Law served as input for estimating five commonly use monomodal PSDs, i.e., Rosin- Rammer distribution, normal distribution, logarithmic normal distribution, modified beta distribution, and Johnson＇s SB distribution. The retrieval results show that the ACO algorithm has high feasibility and reliability, thus providing a new method for the retrieval of PSD.
The ant colony optimization （ACO） algorithm based on the probability density function is applied for the retrieval of spherical particle size distribution （PSD）. The spectral extinction data based on the Mie theory and the Lambert-Beer Law served as input for estimating five commonly use monomodal PSDs, i.e., Rosin- Rammer distribution, normal distribution, logarithmic normal distribution, modified beta distribution, and Johnson＇s SB distribution. The retrieval results show that the ACO algorithm has high feasibility and reliability, thus providing a new method for the retrieval of PSD.
基金
supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.51121004)
the National Natural Science Foundation of China(No.51076037)
the Fundamental Research Funds for the Central Universities(No.HIT.BRET 1.2010012)
