Latin hypercube design (LHD) is one of the most frequently used sampling methods. However, most LHDs generate data samples in a manner that hinders computational efficiency and space-filling performance when high dimensions and large samples are involved. Therefore, a sequential recursive evolution ...
Optimal sampling using Conditioned Latin Hypercube for digital soil mapping: An approach using Bhattacharyya distance 来自 dx.doi.org 喜欢 0 阅读量: 5 作者:A Khan,M Aitkenhead,CR Stark,ME Jorat 摘要: CLH sampling is an effective method for DSM, accounting for environmental covariates.A study on...
In this paper, using uniform design and orthogonal array we give a method of constructing lower discrepancy OA-based Latin hypercube designs. The designs constructed by this method have not only good uniformity and also orthogonality. An... MA Changxing,R Zhang - 《Chinese Journal of Applied Pro...
This paper compares three methods for solving probabilistic optimal power flow (P-OPF) problem: Zhao's point estimate method (PEM), Quasi Monte Carlo simulation (QMCS) and Latin hypercube sampling (LHS). With Nataf transformation, P-OPF problem is formulated as a multiple integral over standard...
Structure and System Nonprobabilistic Reliability Solution Method Based on Enhanced Optimal Latin Hypercube Sampling.Structure and System Nonprobabilistic Reliability Solution Method Based on Enhanced Optimal Latin Hypercube Sampling.doi:10.1142/S0219455414500345Non...
Use a sequential gradient-enhanced-Kriging optimal experimental design method to build high-precision approximate model for complex simulation problem... Y Li,J Shi,J Shen - 《Evolutionary Intelligence》 被引量: 0发表: 2020年 Kriging and Latin Hypercube Sampling Assisted Simulation Optimization in Op...
Probabilistic safety risk assessment in large-diameter tunnel construction using an interactive and explainable tree-based pipeline optimization method 2023, Applied Soft Computing Show abstract Structural analysis and weight optimization of automotive chassis by Latin hypercube sampling using metal matrix compos...
Latin Hypercube Sampling and Partial Rank Correlation Coefficient Analysis Applied to an Optimal Control Problem Latin Hypercube Sampling/Partial Rank Correlation Coefficient (LHS/PRCC) sensitivity analysis is an efficient tool often employed in uncertainty analysis to explore the entire parameter space of ...
A large number of original scenario sets of wind turbine power obeying probability distribution are generated by Latin Hypercube Sampling (LHS) [25], and then the above scenario sets are reduced by the simultaneous back-generation reduction method based on probability distance to derive the ...
2013) proposed a discrete PSO approach, named LaPSO, to search for an optimal Latin hypercube design. The authors accelerated LaPSO by using GPU and showed that the GPU implementation can save computational time significantly for large optimization problems. We expect that the programs in this ...