基于改进差分进化算法的超声衰减谱反演计算

针对传统差分进化算法存在早熟收敛和求解精度低的缺点,研究了一种自适应控制参数的差分进化算法。通过引入自适应控制变量因子、自适应缩放因子和交叉因子使种群不断地向更新成功的个体学习,促进了后续种群的进化。对于颗粒粒径分布服从高斯分布、R-R(Rosin-Rammler)分布以及对数正态分布的3种典型颗粒系进行数值模拟,研究算例发现,改进差分进化算法反演得出分布参数值■,K的误差小于5%,体积中位径相比于设定分布的误差小于5%,因此,改进差分进化算法具有较强的稳定性与抗噪性。

Inverse calculation of ultrasonic attenuation spectrum based on an improved differential evolution algorithm

The traditional differential evolution algorithm frequently encounters the problem of premature convergence and low accuracy. By introducing adaptive control variable factors, a differential evolution (DE) algorithm was developed to ensure that the population could be updated continuously and successfully. The individual learning, which is conducive to the evolution of subsequent populations, and the overall inversion yield more accurate results. As a validation, the particle systems obeying three typical distribution functions of Gaussian distribution, R-R distribution and lognormal distribution were numerically simulated. The resultant distribution parameter values $\bar R $ and K yield errors less than 5%, and the deviations of median volume diameter are within ±5% compared with the given distribution. The DE algorithm also reveals obvious stability and noise resistance.