改进人工鱼群算法在气溶胶粒径分布反演中的应用-中南大学学报.PDF

第 47 卷第 6 期 中南大学学报( 自然科学版) Vol.47 No.6 2016 年 6 月 Journal of Central South University (Science and Technology) June 2016 DOI: 10.11817/j.issn.1672-7207.2016.06.043 改进人工鱼群算法在气溶胶粒径分布反演中的应用 贺振宗，齐宏，贾腾，阮立明 (哈尔滨工业大学 能源科学与工程学院，黑龙江 哈尔滨，150001) 摘要：基于光谱消光法，利用一种改进的人工鱼群算法(improved artificial fish school algorithm，IAFSA)反演单峰 和双峰气溶胶粒子粒径分布。其中，正问题的求解采用反常衍射近似(anomalous diffraction approximation，ADA) 和 Lambert−Beer 定律。研究结果表明：相对标准人工鱼群算法而言，IAFSA 能很好地避免出现后期收敛速度慢、 精度低等问题。在非独立模型下反演气溶胶粒径分布时，IAFSA 算法体现出很好的收敛精确度和鲁棒性。在非独 立模型下，IAFSA 算法可用于反演实际测量得到的哈尔滨地区气溶胶粒径分布。 关键词：气溶胶；改进人工鱼群算法；粒径分布 中图分类号：TP212 文献标志码：A 文章编号：1672−7207(2016)06−2141−06 Application of improved artificial fish school algorithm in retrieving aerosol particle size distribution HE Zhenzong, QI Hong, JIA Teng, RUAN Liming (School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, China) Abstract: Based on the spectral extinction method, an improved artificial fish school algorithm (IAFSA) was employed to retrieve the monomodal and bimodal aerosol size distributions. The direct problem was solved by the anomalous diffraction approximation (ADA) and Lambert−beer law. The results show that IAFSA can overcome low convergence rate and accuracy, compared with AFSA. Moreover, in retrieving the aerosol size distribution with the dependent model, the IAFSA shows satisfactory convergence accuracy and robustness. IAFSA can be employed to estimate the actual aerosol size distribution over Harbin with the independent model. Key words: aerosol; improved artificial fish school algori