In order to utilize original sampling points as many as possible to construct a Latin Hypercube Sampling (LHS), a generation algorithm of LHS is proposed. The original sampling can be an arbitrary sampling and the new...
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ISBN:
(纸本)9788897999485
In order to utilize original sampling points as many as possible to construct a Latin Hypercube Sampling (LHS), a generation algorithm of LHS is proposed. The original sampling can be an arbitrary sampling and the new sampling is a LHS strictly. As the high structure of LHS, only part of original sampling points can be used for LHS. There are several problems including how to select the reserved original sampling points and generate the new ones if necessary. Matrices are used to describe the original sampling points and the original sampling points are reserved based on an adjacent matrix. The new sampling points are generated by a subtraction rule. Numerical experiments show that the generation algorithm is effective and saves a lot of running time for simulationsystems.
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