Latin hypercube sampling (LHS) is one technique that stands out in this context. LHS selects representative samples through permutations in a multidimensional space, effectively preventing the clustering of points in specific areas. However, its limitations become apparent in high-dimensional problems, ...
The SA has been carried out considering more than 100 samples and mostly Simple Random Sampling (SRS), but also Latin Hypercube Sampling (LHS) methods were tested. Table 9. Core cases: parameters and distributions used for the SA. At the core level, several figures of merit (reactivity, ...
(2022) compared MLMC and Latin hypercube sampling (LHS) to traditional FMC, testing both speed and accuracy. Four time limits were used to show the increased accuracy under realistic time constraints; minimum costs for convergence of the output distribution were investigated across the three methods...
as deterministic. A widely used, random sampling methods for parameter estimation, albeit costly, is the Markov chain Monte Carlo (MCMC) [151] algorithms, however the number of simulations involved rapidly becomes prohibitive since they are based on the Markov chain process which requires a very h...
The Latin Hypercube Sampling method was utilized for the analysis. For a separate member, the computational model was formed by analytical solution, for the calculation of the load–carrying capacity of steel plane frame, the geometrical nonlinear finite element solution providing numerical result per ...
(2003). On Latin hypercube sampling for structural reliability analysis. Structural Safety, 25, 47–68. CrossRef Helton, J. C., & Davis, F. J. (2003). Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering and System Safety, 81,...
6.1.1. Latin Hypercube Sampling Distribution The performance error and regression coefficient between the predicted and actual output data are shown in Figure 16 for the case of data distributed according to the LHS algorithm. Each bar corresponds to one size of the hidden layer of the ANN (i....
mRNA-based therapeutics are predicted to have a bright future. Recently, a B2C study was published highlighting the critical bottlenecks of mRNA manufacturing. The study focused on supply bottlenecks of various chemicals as well as shortages of skilled p
1Citations Metricsdetails Abstract A non-intrusive reduced-order model based on convolutional autoencoders is proposed as a data-driven tool to build an efficient nonlinear reduced-order model for stochastic spatiotemporal large-scale flow problems. The objective is to perform accurate and rapid uncer...
(i) Incorporation of the contribution of expert committees into expert systems, (ii) Replacement of response surface functions with Latin hypercube sampling (LHS). (iii) Automation of a significant portion of the process, (iv) Proof-of-principle application of the methodology assessed based on ...