Rajabi, Mohammad Mahdi, Behzad Ataie-Ashtiani, and Hans Janssen. 2015. "Efficiency Enhancement of Optimized Latin Hypercube Sampling Strategies: Application to Monte Carlo Uncertainty Analysis and Meta-Modeling." Advances in Water Resources 76: 127-139....
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...
The Latin hypercube sampling is optimized by simulated annealing algorithm. Based on the improved PSO-BP neural network, the metamodel between drawbead ... Yanmin,Xie,Wencheng,... - 《Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design & Applications》 被引量...
The Latin Hypercube Sampling method is used to simulate wind power uncertainty, clearly defining backup compensation costs for insufficient wind output and wind curtailment costs for excess output. By incorporating the carbon trading mechanism based on wind power’s impact on system dispatch, ...
(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-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 ...
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, ...
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...