Efficiency enhancement of optimized Latin hypercube sampling strategies: application to Monte Carlo uncertainty analysis and meta-modeling. Adv. Water Resour. 76, 127-139.Rajabi, M.M.; Ataie-Ashtiani, B.; Janssen, H. Efficiency enhancement of optimized Latin hypercube sampling strategies: Application...
The combination of an optimized Latin hypercube sampling method and expected improvement (EI) points infill criteria is to improve surrogate modeling efficiency. The NREL 5 MW wind turbine blade was used as the research object. The NACA64618 with 18% relative thickness, the DU91-W2-250 with 25...
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...
Sampling efficiency in Monte Carlo based uncertainty propagation strategies: Application in seawater intrusion simulations Monte Carlo methodsSampling efficiencyOptimized Latin hypercube samplingThe implementation of Monte Carlo simulations (MCSs) for the propagation of uncertainty in... MM Rajabi,B Ataie-Asht...
In terms of algorithm improvement, three improvements are proposed for SSA: Latin hypercube sampling is introduced to initialize the location of sparrows and increase the diversity of sparrows; the somersault foraging strategy is used to enrich the optimal position of producers; and combining with the...
(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 ...
Latin hypercube samplingMulti-objective optimizationEnvironmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in ...