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Design point choice of Gaussian process response surface model applied to uncertainty analysis

LIU Xin'en,XIAO Shifu,MO Jun(Institute of Systems Engineering,China Academy of Engineering Physics,Mianyang 621900,Sichuan,China)  
An efficient method of design point choice is presented,which can automatically optimize the location of the points,to advance the application of Gaussian process response surface model to uncertainty analysis of the complex time-consuming numerical simulation.The method produces the design points in a standard Latin hypercube,and then maps them back to the original design space according to the known probability distribution of input variables.The method and the traditional Latin Hypercube Design method based on an assumed uniform distribution are compared and their effect on the established Gaussian process response surface model and uncertainty analysis result is discussed.An example indicates the advantage of the method.
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