中南大学学报（自然科学版）2016，Vol.47Issue(11)：3922-3928,7.DOI:10.11817/j.issn.1672-7207.2016.11.040
基于RQPSO的颗粒粒径分布反演算法
Retrieval of particle size distribution based on RQPSO algorithm
摘要
Abstract
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.关键词
粒径分布/量子微利群算法/正则化/光全散射法/独立模式Key words
particle size distribution/quantum behavior particle swarm optimization/regularization/total light scattering/independent mode分类
信息技术与安全科学引用本文复制引用
张彪,李舒,许传龙,王式民..基于RQPSO的颗粒粒径分布反演算法[J].中南大学学报（自然科学版）,2016,47(11):3922-3928,7.基金项目
国家自然科学基金资助项目(51506030,51376049)；江苏省自然科学基金资助项目(BK20150622)；国家质量监督检验检疫总局科技计划项目(2012QK176)(Projects(51506030,51376049) supported by the National Natural Science Foundation of China （51506030,51376049）
Project(BK20150622) supported by the Natural Science Foundation of Jiangsu Province （BK20150622）
Project(2012QK176) supported by the State Administration of Quality Supervision, Inspection and Quarantine Science and Technology) （2012QK176）
