To solve the problem with the surrogate model method, an optimal Latin hypercube sampling (OLHS) technique and a two-phase differential evolution (ToPDE) algorithm were utilized to generate calculation points in the design space, respectively. Then different surrogate models including the RSM model,...
The Latin hypercube sampling conducted very less iterations and is based on response probability stratification [32]. Show abstract FE design analysis and optimization of heavy-duty truck chassis using sparse grid initialization technique 2022, Materials Today: Proceedings Citation Excerpt : Taking into ...
1. Parameters are sampled and substituted by Latin Hypercube Sampling (LHS) technique [41] (a valid statistical scheme for multidimensional distribution to obtaining parameter sample values). Total simulations of 1000 were carried out. The baseline parameter values of Table 2 were changed in 25% ...
To solve the problem with the surrogate model method, an optimal Latin hypercube sampling (OLHS) technique and a two-phase differential evolution (ToPDE) algorithm were utilized to generate calculation points in the design space, respectively. Then different surrogate models including the RSM model,...
Latin hypercube samplingIn this article, the Latin hypercube sampling (LHS) based probabilistic optimal power flow (P㎡PF) technique is employed to assess the performance of power systems under large wind power penetration. In the case where only wind speed samples are available, the kernel tuned...
The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored.We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the ...
Optimal Latin Hypercube (OLH)Radial Basis Function (RBF) Neural NetworkThis paper presents the application of iSight for optimal tip design of complex tool holder spindle. The complex tool holder is used for holding a (milling/drilling) tool of a machine tool. The engineering problem of complex...
To address these uncertainties, the paper employs scenario modeling techniques named as Latin hypercube sampling with Cholesky decomposition. This technique generates multiple correlated scenarios that represent uncertain variables. Subsequently, a scenario reduction technique is applied to identify the sc...
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 ...
Latin hypercube sampling Latin Hypercube Sampling (LHS) is a stratified sampling technique to generate near-random samples from a prob- ability distribution [38]. To generate N samples from D variables, the range of each variable is divided into N equally probable intervals. From each interval, ...