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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
