In order to explore the entire domain represented by interval variables, an enhanced optimal Latin hypercube sampling (EOLHS) is used to reduce the computational effort considerably. Through the proposed method,
8, it would be then applied into the optimal design system along with the Latin Hypercube Sampling (LHS) methodology, the Computational Fluid Dynamic (CFD) analysis, and the Multi-Objective Particle Swarm Optimization (MOPSO) method. Fig. 9 shows the flow chart of the optimal design system, ...
American put option using the combined PINN. Commonly used grid generation methods include uniform grid, equispaced grid, Latin hypercube sampling, and so on. Pricing analysis of American options by generating a grid is also used in the finite difference method. Kwok et al36. gave an equispaced...
Latin Hypercube sampling is performed to generate input data for rigorous Aspen Plus simulations. Piecewise linear surrogate models are derived by solving GDP problems based on high-fidelity data from Aspen Plus and nonlinear capital cost correlations. In the following step, a hybrid MILP master ...
If people want to quickly obtain the solution of the engineering scheme, perhaps some simple heuristic algorithms such as Latin hypercube sampling could be more recommended. But we cannot guarantee the result validity of these algorithms. Fortunately, we do not need to worry about the validity ...
The simulated solutions of the model were analyzed using MAPLE-18 with Runge–Kutta–Felberg method (RKF45 solver). The model entrenched parameters analysis revealed that there are both disease-free and endemic equilibrium points. The solutions depicted that the free equilibrium point for COVID-19 ...
The method divides the criterion space into a set of hypercubes of length ε (for 2 criteria, this is a square). Then all the PF solutions located in the same hypercube are ε-dominated to each other. In this case, we can select a smaller set of solutions by taking only one solution...
It is noted that the Monte Carlo (MC) simulation is often applied to generate wind power samples to conduct sto- chastic optimization in the probabilistic method [21–23]. However, the MC method is notorious for its heavy com- putation burden. Thanks to the Latin hypercube sampling with ...
Similar to the Latin Hypercube Sampling (LHS) method, OSF has no requirement for the number of samples as the dimension of variables increases as they both divide the entire design space into many levels, which equals the number of samples and draws samples from different locations. Show ...
Latin hypercube method was applied to simulate the uncertain inflow, and its sampling frequency and accuracy were very satisfied. Linear regression method was used to deal with the damping and deformation in the process of flow transmission. And Genetic algorithm(GA) was...