最佳拉丁超立方试验设计方法被用来生产数据样本。
Optimal Latin hypercube experimental design method was used to produce data samples.
另一方面，为顾及概率分布的尾部特征，提出拉丁超立方重要抽样技术。
On the other hand, Latin hypercube important sampling technique was presented to consider the tail of distribution.
通过不同规模和不同优化准则的拉丁超立方体最优实验设计，验证改进算法的应用效果。
The application results of the improved algorithm are verified by searching Latin hypercube optimal design of varying scales under different optimization criteria.
本文将拉丁超立方抽样法与条件期望和对偶变数方差减缩技术组合用于分析船体总纵极限强度可靠性。
This paper proposes Latin hypercube sampling combined with variance reduction techniques of conditional expectation and antithetic variates to assess ultimate strength reliability of ship hull girder.
综合应用析因试验设计与拉丁超立方抽样试验设计，对难加工材料马氏体不锈钢进行了高速铣削试验。
Factorials design and Latin hypercube sampling design are applied in the high-speed milling experiments of martensitic stainless steel.
为了减少随机抽样的次数并保证蒙特卡罗法的数值模拟精度，对比引入了重要抽样法和拉丁超立方体抽样方法；
To reduce sampling number and assure simulation precision, Importance Sampling method and Latin Hypercube Sampling method are coupled with Neumann expansion SFEM respectively.
本文采用概率方法借助于拉丁超立方采样技术和非线性地震反应时程分析对多层住宅砖房的地震易损性进行分析。
This paper analyzes the seismic vulnerability of multistory dwelling brick buildings by Latin Hypercube Sampling technique and nonlinear seismic time history response analysis.
在一系列不同的极限状态函数条件下，对随机抽样法和拉丁超立方抽样法以及是否使用方差减缩技术进行了比较研究。
Comparative study on random sampling and Latin hypercube sampling with and without variance reduction techniques is carried out to a number of different limit state functions.
最后通过GA - BP神经网络与拉丁超立方抽样法相结合构建了可控拉深筋主要影响因子h1和H2与极限拉深深度之间的响应面。
Eventually, the response surfaces composed of the CD main influence factor H1, H2 and limit drawing depth are established by the combination of GA-BP neural network and Latin Hypercube.
最后通过GA - BP神经网络与拉丁超立方抽样法相结合构建了可控拉深筋主要影响因子h1和H2与极限拉深深度之间的响应面。
Eventually, the response surfaces composed of the CD main influence factor H1, H2 and limit drawing depth are established by the combination of GA-BP neural network and Latin Hypercube.
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