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Dust Particle Size Distribution Inversion Based on the Multi Population Genetic Algorithm

机译:基于多种群遗传算法的粉尘粒径分布反演

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摘要

The aerosol number size distribution is the main parameter for characterizing aerosol optical properties and physical properties, it has a major influence on radiation forcing. With regard to some disadvantages in the traditional methods, a method based on the multi population genetic algorithm (MPGA) is proposed and employed to retrieve the aerosol size distribution of dust particles. The MPGA principles and design are presented in detail. The MPGA has better performance compared with conventional methods. In order to verify the feasibility of the inversion method, the measured aerosol optical thickness (AOT) data of dust particles taken by a sun photometer are used and a series of comparisons between the simple genetic algorithm (SGA) and MPGA are carried out. The results show that the MPGA presents better properties when compared with the SGA with smaller inversion errors, smaller population size and fewer generation numbers to retrieve the aerosol size distribution. The MPGA inversion method is analyzed using the background day, dust storm event and seasonal size distribution. The method proposed in this study has important applications and reference value for aerosol particle size distribution inversion.
机译:气溶胶数大小分布是表征气溶胶光学性质和物理性质的主要参数,它对辐射强迫具有重要影响。针对传统方法的一些弊端,提出了一种基于多种群遗传算法(MPGA)的方法,用于获取尘埃颗粒的气溶胶粒径分布。详细介绍了MPGA的原理和设计。与传统方法相比,MPGA具有更好的性能。为了验证该反演方法的可行性,使用了由日光光度计测得的尘埃颗粒的气溶胶光学厚度(AOT)数据,并对简单遗传算法(SGA)和MPGA进行了一系列比较。结果表明,与SGA相比,MPGA具有更好的性能,具有较小的反演误差,较小的种群规模和较少的世代数,可检索气溶胶粒径分布。使用背景日,沙尘暴事件和季节大小分布分析了MPGA反演方法。本研究提出的方法对气溶胶粒径分布反演具有重要的应用和参考价值。

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