系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2010年
11期
2089~2098
,共null页
黄寒砚 王正明 陈璇 王菖
黃寒硯 王正明 陳璇 王菖
황한연 왕정명 진선 왕창
Kriging模型 计算机试验 序贯试验设计 不平稳协方差 均匀设计 预测不确定性
Kriging模型 計算機試驗 序貫試驗設計 不平穩協方差 均勻設計 預測不確定性
Kriging모형 계산궤시험 서관시험설계 불평은협방차 균균설계 예측불학정성
Kriging meta-modeling; computer experiments; sequential design of experiment; non-stationary covariance; uniform design; prediction uncertainty
在工业设计中常涉及复杂、耗时的仿真,建立简单的近似模型可以简化分析和优化过程.元模型的构建和仿真试验的设计是其中的两个关键问题.针对元模型的构建,分析指出传统的基于平稳性假设的Kriging方法并不适合常见的不规则系统的建模,接着采用非线性映射方法,提出了一种基于不平稳假设的Kriging方法.实例说明:相对于传统的Kriging方法,该方法不仅可以建立精度较高的预测模型,而且对模型的预测不确定性的描述也更符合直观认识;针对计算机试验设计,提出了一种基于改进的Kriging方法的序贯准则,使得试验点序贯产生在不确定性大且距离现有试验点远的位置.算例表明:该序贯设计比一步设计效果好,能节约试验样本.
在工業設計中常涉及複雜、耗時的倣真,建立簡單的近似模型可以簡化分析和優化過程.元模型的構建和倣真試驗的設計是其中的兩箇關鍵問題.針對元模型的構建,分析指齣傳統的基于平穩性假設的Kriging方法併不適閤常見的不規則繫統的建模,接著採用非線性映射方法,提齣瞭一種基于不平穩假設的Kriging方法.實例說明:相對于傳統的Kriging方法,該方法不僅可以建立精度較高的預測模型,而且對模型的預測不確定性的描述也更符閤直觀認識;針對計算機試驗設計,提齣瞭一種基于改進的Kriging方法的序貫準則,使得試驗點序貫產生在不確定性大且距離現有試驗點遠的位置.算例錶明:該序貫設計比一步設計效果好,能節約試驗樣本.
재공업설계중상섭급복잡、모시적방진,건립간단적근사모형가이간화분석화우화과정.원모형적구건화방진시험적설계시기중적량개관건문제.침대원모형적구건,분석지출전통적기우평은성가설적Kriging방법병불괄합상견적불규칙계통적건모,접착채용비선성영사방법,제출료일충기우불평은가설적Kriging방법.실례설명:상대우전통적Kriging방법,해방법불부가이건립정도교고적예측모형,이차대모형적예측불학정성적묘술야경부합직관인식;침대계산궤시험설계,제출료일충기우개진적Kriging방법적서관준칙,사득시험점서관산생재불학정성대차거리현유시험점원적위치.산례표명:해서관설계비일보설계효과호,능절약시험양본.
Surrogate models are usually developed to facilitate the analysis and optimization of engineering systems that involve computationally expensive simulations.The two key problems in constructing the surrogate model are meta-modeling and design of computer experiment.As for the meta-modeling,the widely used Kriging method is under the assumption of a stationary covariance structure,which does not hold in situations where the level of smoothness of a response varies significantly.Thus,we adopt a non-linear mapping approach to incorporate the non-stationary covariance structure into Kriging meta-modeling for simulations.Examples show that the proposed method is superior to the classical Kriging method in producing kriging meta-models with higher prediction accuracy and in quantifying prediction uncertainty associated with the use of meta-models.As for the design of computer experiment,we proposed a sequential criterion based on the improved Kriging method to generate new design points with high prediction uncertainty and with great distance to the current design points.Examples show that the sequential design is superior to the single-stage design in saving samples.