| 基于Kullback-Leibler距离离散度的加权代理模型 |
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| 引用本文： | 晏良,段晓君,刘博文,徐琎.基于Kullback-Leibler距离离散度的加权代理模型[J].国防科技大学学报,2019,41(3):159-165. |
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| 作者姓名： | 晏良 段晓君 刘博文 徐琎 |
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| 作者单位： | 国防科技大学 文理学院,湖南 长沙,410073;国防科技大学 文理学院,湖南 长沙,410073;国防科技大学 文理学院,湖南 长沙,410073;国防科技大学 文理学院,湖南 长沙,410073 |
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| 基金项目： | 国家自然科学基金资助项目（11771450，61573367） |
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| 摘 要： | 复杂系统的仿真通常具有高维度、高计算量等特点，代理模型因其明晰的数学表达和良好的计算特性可用于逼近真实系统。加权模型对比单个代理模型来说，其稳定性和适应性更广。不同的代理模型其性能不一，根据特定指标，可以构造最优加权代理模型。基于代理模型预测分布以及Kullback-Leibler距离构造各子代理模型之间的离散度，并提出一种新的权函数构造方法。算例表明，该方法与最优子模型的精度相当，同时能提高对真实响应分布的逼近。
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| 关 键 词： | 复杂系统 代理模型 Kullback-Leibler距离 |
| 收稿时间： | 2018/3/25 0:00:00 |
Weighted surrogate models based on Kullback-Leibler divergence |
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| YAN Liang,DUAN Xiaojun,LIU Bowen and XU Jin.Weighted surrogate models based on Kullback-Leibler divergence[J].Journal of National University of Defense Technology,2019,41(3):159-165. |
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| Authors: | YAN Liang DUAN Xiaojun LIU Bowen and XU Jin |
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| Affiliation: | College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China,College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China,College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China and College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China |
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| Abstract: | Surrogate methods (metamodels) are convenient to determine the mathematical relationship underlying the high dimensional complex systems, which are usually computationally expensive. Various stand-alone metamodels have been proposed in literature, and the ensemble of metamodels was being intensively studied recently to utilize the information reveals in construction of different metamodels. Compared with the stand-alone metamodels, the ensembled models were more robust and adaptable. The strategy of the ensemble by comparing the difference of the probability distribution of predictions was considered, where the Kullback-Leibler divergence was introduced to calculate the differences. Experiments show that the strategy has comparable accuracy in predictions with the most accurate stand alone metamodel, and it can also perform better in recovering the distribution of the true response. |
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| Keywords: | complex systems surrogate models Kullback-Leibler divergence |
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