多情景源排放参数反演下典型优化算法性能对比

Performance of Typical Optimization Algorithms on Inversing Multi-scene Source Parameters

确定排放源参数是合理处置突发大气污染事故的重要前提.不同事故(如泄漏、火灾)反演的参数(源强、位置等)存在差异,研究对比不同优化算法的估算性能对于实际事故中快速、准确估算源参数具有重要意义.基于草原SO2释放实验数据,开展了不同未知参数情景下典型最优化算法(遗传算法,GA;粒子群算法,PSO;粒子群-单纯形耦合算法,PSO-NM)在源参数反演中的对比研究,从反演结果的准确性、稳定性与反演时间效率等方面进行了评估.研究发现,优化算法在不同源排放参数数量下的反演性能存在明显差异.单参数源强反演情形下,GA、PSO-NM算法准确性相近(相对偏差,24.0%),均优于PSO算法(37.6%),三者均有较好的反演稳定性(变异系数<0.004);多参数反演(源强Q与位置x、y、z)情形下,PSO-NM算法反演准确性最好,GA最差,但稳定性表现与之相反;反演参数数量的增加明显影响算法反演稳定性,四维参数反演情形下PSO、GA、PSO-NM算法的源强反演变异系数比单参数反演分别高出0.50、0.12、0.29.PSO算法计算效率最高,同时,PSO-NM算法在稳定大气条件下计算时间明显增加.

Determination of release source parameters of hazardous pollutants is an important basis for adequate disposal on sudden air pollution accidents.The parameters(source strength,location,etc.)needed to be estimated for different accidents(such as leakage and fire)are different.It is of great significance to study and compare the estimation performance of different optimization algorithms for fast and accurate estimation of source parameters in actual accidents.Based on the SO2 release experimental data of 1956 Prairie Grass field experiments,a comparative evaluation study on the application of typical optimization algorithms,including genetic algorithm(GA),particle swarm optimization(PSO)and particle swarm optimization-simplex coupling algorithm(PSO-NM),in source parameter inversion under different scenarios of unknown parameters was carried out in this paper.The inversion accuracy,stability and time cost of different optimization algorithms were analyzed and discussed.Results show that the inversion performances of various optimization algorithms are significantly distinct when inversing different emission parameters.In the case of single-parameter inversion(only the source strength is unknown),GA and PSO-NM have similar accuracy with absolute value of relative deviation of 24.0%,better than that of PSO algorithm(37.6%);and all the three algorithms have better inversion stability with coefficient of variation of less than 0.004.In the case of multi-parameter inversion(source strength Q and position x,y and z),PSO-NM has the best and GA has the worst inversion accuracy,however,the performance of robustness is opposite.Additionally,the increase of the number of inversion parameters obviously affects the inversion robustness of different algorithms.The coefficients of variation for source strength inversion when inversing the four parameters are higher than those of single-parameter inversion by 0.50,0.12 and 0.29 for PSO,GA and PSO-NM,respectively.For the time cost,the PSO algorithm performs best;PSO-NM algorithm shows a significant increase in calculation time cost under stable atmospheric conditions.