针对标准量子微粒群算法(BQPSO)，提出改进量子微粒群算法(IQPSO)和含正则化项的改进量子微粒群算法(RQPSO)，并将它们引入到粒径分布的反演中，利用光全散射法在独立模式下，通过测量可见光波段内不同波长下的光谱消光值反演几种粒径分布，其中正问题利用反常衍射近似(ADA)计算得到估计值，测量值则通过Mie理论计算得到。研究结果表明：与BQPSO相比，IQPSO在计算效率和稳定性上得到很大提升；在粒径分布的反演中，RQPSO提高IQPSO的维数极限，并具有更高的反演精度、稳定性和抗噪性，为粒径分布的反演提供一种新的方法。%An improved quantum behavior particle swarm optimization (IQPSO) and regularized quantum behavior particle swarm optimization (RQPSO) were developed based on basic quantum behavior particle swarm optimization (BQPSO). Furthermore, these three algorithms were introduced in retrieval of particle size distribution (PSD). Several types of PSDs were retrieved by measuring the spectral extinction values in the visible spectrum, which used total light scattering method under independent mode. In the direct problem, the anomalous diffraction approximation was used to calculate the estimation values, and Mie theory was used for measurement values. The results show that the efficiency and stability of the IQPSO algorithm was proved to be more greatly improved than the BQPSO algorithm. For the retrieval of these PSDs, the RQPSO algorithm has better performances on dimension limit, accuracy, stability and noise immunity than the IQPSO algorithm. Thus, this algorithm provides a new method for retrieving of PSDs.
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