BRDF的遗传算法和遗传模拟退火算法建模及比较

doi:10.3969/j.issn.1001506X.2010.07.041

Journal of Systems Engineering and Electronics ›› 2010, Vol. 32 ›› Issue (7): 1529-1531.doi: 10.3969/j.issn.1001506X.2010.07.041

BRDF的遗传算法和遗传模拟退火算法建模及比较

张涵璐, 吴振森, 张昌民, 曹运华

(西安电子科技大学理学院，陕西西安 710071)

出版日期:2010-07-20 发布日期:2010-01-03

Modeling and comparison of BRDF with GA and GSAA

ZHANG Hanlu, WU Zhensen, ZHANG Changmin, CAO Yunhua

(School of Science, Xidian Univ., Xi’an 710071， China)

Online:2010-07-20 Published:2010-01-03

摘要/Abstract

摘要：

结合遗传算法和模拟退火算法，构造出具有全局搜索优化特性的遗传模拟退火算法。根据空间目标表面的多组多角度双向反射分布函数（bidirectional reflectance distribution function， BRDF）实验数据和统计模型，获得样片BRDF五参数模型参数值及2D、3D的BRDF分布。比较基本遗传算法和遗传模拟退火算法在迭代次数、计算时间、参数值及精度等之间的差异并分析其原因。遗传模拟退火算法更适用于BRDF的统计建模。

Abstract:

Combining the basic genetic algorithm (GA) with the simulated annealing algorithm, a genetic simulated annealing algorithm (GSAA) is obtained with the character of global searching and optimum. Both GA and GSAA are used to fit bistatic mulitiangle data of experiment to the bidirectional reflectance distribution function (BRDF) statistical model. The parameters of the model and the 2D and 3D BRDF are obtained. The differences and causations between GA and GSAA in the iterative numbers, time, precision, data fitting and parameters are compared and analyzed. GA and GSAA held for BRDF statistic modeling.

张涵璐, 吴振森, 张昌民, 曹运华. BRDF的遗传算法和遗传模拟退火算法建模及比较[J]. Journal of Systems Engineering and Electronics, 2010, 32(7): 1529-1531.

ZHANG Hanlu, WU Zhensen, ZHANG Changmin, CAO Yunhua. Modeling and comparison of BRDF with GA and GSAA[J]. Journal of Systems Engineering and Electronics, 2010, 32(7): 1529-1531.

BRDF的遗传算法和遗传模拟退火算法建模及比较

Modeling and comparison of BRDF with GA and GSAA

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