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Asian Simulation Conference

SCS Autumn Simulation Multi-Conference

AsiaSim 2016, SCS AutumnSim 2016: Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems pp 176–185Cite as

A Sequential Latin Hypercube Sampling Method for Metamodeling

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 643))

Abstract

For utilizing the original sampling points and improving budget allocation efficiency, we propose a sequential Latin Hypercube Sampling (LHS) method for metamodeling. The sequential method starts with an original LHS of size n and constructs a new LHS of size kn that has the original points as more as possible. The sampling points of LHS are described by some matrixes and it is proved that there is no need to delete original points for the new LHS. A subtraction rule is applied for adding new sampling points. The original and addition sampling points are proved to be a strict LHS. The method is applied for metamodeling to demonstrate the effectiveness.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Grant No. 61403097).

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Authors and Affiliations

  1. Control and Simulation Center, Harbin Institute of Technology, Harbin, China

    Zhizhao Liu, Ming Yang & Wei Li

Authors
  1. Zhizhao Liu
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  2. Ming Yang
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  3. Wei Li
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Corresponding author

Correspondence to Wei Li .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Lin Zhang

  2. Beihang University, Beijing, China

    Xiao Song

  3. Beihang University, Beijing, China

    Yunjie Wu

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© 2016 Springer Science+Business Media Singapore

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Liu, Z., Yang, M., Li, W. (2016). A Sequential Latin Hypercube Sampling Method for Metamodeling. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-10-2663-8_19

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  • DOI: https://doi.org/10.1007/978-981-10-2663-8_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2662-1

  • Online ISBN: 978-981-10-2663-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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