光散射模型参量反演中的遗传模拟退火算法

为了研究遗传模拟退火算法在光散射模型参量反演中的迭代搜索性能问题,分别采用遗传模拟退火算法和单一遗传算法迭代搜索了几种介质的双向反射分布函数模型的相关参量。将两种算法的反演结果与在特定激光波长下的双向反射分布函数实验数据进行了对比,通过理论分析和实验验证,取得了两种算法所得到的拟合值,两种拟合值都与实验数据吻合得较好;同时比较了遗传模拟退火算法和单一遗传算法在迭代次数、计算时间和均方误差等之间的差异。结果表明,两种算法在不同介质表面双向反射分布函数模型参量反演时都可以得到满意的结果,且前者优化效果更优。这一结果对研究不同算法的迭代搜索性能是有帮助的。

Application of Genetic Simulated Annealing Algorithms Based on the Parameters Reverse of BRDF Model

The method that the parameter of the BRDF model of the object sample obtained by using the Genetic Simulated Annealing Algorithm was introduced. The parameter of BRDF model was obtained when the Genetic Simulated Annealing Algorithm and Genetic Algorithm were applicable to the parameter in reverse of the BRDF statistic model of the object surface according to the BRDF experimental data at the laser wavelength (1.06μm). The curve indicated that the experimental data fitted accorded with those optimized by using the Genetic Simulated Annealing Algorithm better than by using Genetic Algorithm, which showed that the results consistency obtained by Genetic Simulated Annealing Algorithm.