Rajabi, M., Ataie-Ashtiani, B., Janssen, H., 2015a. Efficiency enhancement of optimized Latin hypercube sampling strategies: application to Monte Carlo uncertainty analysis and meta-modeling. Adv. Water Resour. 76, 127-139.Rajabi MM, Ataie-Ashtiani B, Janssen H. Efficiency enhancement of ...
(CFD) method andMatlab program, respectively. To reduce the number of CFD calculations, a Krigingsurrogate modelwas established. The combination of an optimizedLatin hypercube samplingmethod and expected improvement (EI) points infill criteria is to improve surrogate modeling efficiency. The NREL 5 MW...
aRelative to simple stratified sampling, the biggest advantage of Latin hypercube sampling is that the number of samples of any size can bemore easily produced. 相对简单的分层取样,拉丁hypercube采样的最大的好处是所有大小罐头bemore样品的数量容易地生产了。 [translate] aat a barbershop recently , ...
(DNN), the algorithmic framework is able to converge towards the target spectrum after sampling 120 conditions. Once the dataset is large enough to train the DNN with sufficient accuracy in the region of the target spectrum, the DNN is used to predict the colour palette accessible with the ...
Latin hypercube samplingsample size extensionspace-fillingLatin hypercube sampling (LHS), as an efficient sampling method, has been widely used in computer experiments. But it is difficult to choice the sample size while applying LHS, especially for expensive simulations. The effective way...
Latin hypercube samplingsample size extensionspace-filling(2017). A novel extension algorithm for optimized Latin hypercube sampling. Journal of Statistical Computation and Simulation: Vol. 87, Special Issue: Selected Papers from 2016 International Simulation Multi-Conference, October 2016, Beijing, China,...
In this work a systematic procedure for multidimensional sensitivity analysis in the area of air pollution modeling by an optimized latin hypercube sampling has been done. The Unified Danish Eulerian Model (UNI-DEM) is used in our investigation, because this is one of the most advanced large-...
importance samplingLatin hypercube sampingreliability analysisThe pivotal problem in reliability analysis is how to use as few actual assessments as possible to obtain an accurate failure probability. Although adaptive Kriging provides a viable method to address this problem, unsatisfied Kriging surrogate ...
latin hypercube samplinggenetic algorithmsThis chapter examines the problem of the resource allocation in degradable road transport networks within a stochastic evolutionary optimization framework. This framework expresses the stochastic equilibrium Network Design Problem (NDP) as a game-theoretic, combinatorial...
Firstly, the Latin Hypercube Sampling method is used to generate the experiment samples for the design of experiments. Secondly, ANSYS Polyflow software is adopted to execute the computational fluid dynamics analysis. Thirdly, the Kriging method is used to generate the response surface. Finally, ...