摘要
根据已测K9玻璃和晶体(ZnS,MgF_2,Calcite)的实验数据,将遗传模拟退火算法应用于修正的Sellimeier方程的参数反演中,建立了上述材料的色散方程。同时比较了遗传模拟退火算法和遗传算法(包括标准遗传算法和多种群遗传算法)在迭代搜索性能方面的差异。结果表明:遗传模拟退火算法的优化效果最优并且性能最稳定。同时,将通过遗传模拟退火算法所得K9玻璃和晶体在某一光谱区域的色散方程应用于其他光谱区域中,发现色散方程的拟合值与实验值符合较好,这表明通过该方法所得色散方程具有较好的外推性。因此,通过遗传模拟退火算法进行色散方程的参量反演方法可以用于其他材料色散方程的拟合。
According to the experimental data of K9 glass, ZnS crystal, MgF2 crystal and calcite crystal, the dispersion equations of the materials was established by the application of genetic simulated annealing algorithm to retrieval parameter of the modified sellmeier equation. Meanwhile, the differences in iteration searching properties between the genetic simulated annealing algorithm and the genetic algorithms including standard genetic algorithm and multi-population genetic algorithm were compared. The results show that the genetic simulated annealing algorithm possesses the best optimization effect and stable performance. Finally, the dispersion equations of K9 glass and crystals obtained by genetic simulated annealing algorithm in one spectral region are used in another spectral region, and the fitted values of dispersion equation are in good agreement with experimental data, indicating that the dispersion equation has better extrapolation. Therefore, retrieval parameter of dispersion equation using genetic simulated annealing algorithm can be applied to other materials.
出处
《红外与激光工程》
EI
CSCD
北大核心
2015年第11期3197-3203,共7页
Infrared and Laser Engineering
基金
陕西省自然科学基金(2012JM1011)
陕西省教育厅科研项目(14JK1301)
陕西省普通高校重点学科建设专项资金(2008)169
关键词
标准遗传算法
多种群遗传算法
遗传模拟退火算法
色散方程
反演
外推性
standard genetic algorithm
multiple population genetic algorithm
genetic simulated annealing algorithm
dispersion equations
retrieval
extrapolation
