2010. Conditioned Latin Hypercube Sampling: Optimal Sample Size for Digital Soil Mapping of Arid Rangelands in Utah, USA. In: J.L. Boettinger et al. (eds.), Digital Soil Mapping, Progress in Soil Science 2, Springer Neatherlands, Dordrecht, Neatherlands. p.67-75....
A large number of original scenario sets of wind turbine power obeying probability distribution are generated by Latin Hypercube Sampling (LHS) [25], and then the above scenario sets are reduced by the simultaneous back-generation reduction method based on probability distance to derive the ...
Using the trained model, a set of candidate solutions can be generated by a variety of inexpensive generative techniques such as Opposition-based Learning and Latin Hypercube Sampling in both objective and decision spaces. Iteratively generated non-dominated candidate solutions cover the initial PF ...
The version of MATLAB we used is R2015b. We first download the codes from “Part H1: Locally D-optimal design for Poisson regression model with M = 2” from the website. Upon typing “run” in the command window, a Graphic User Interface (GUI) pops up as is shown in Fig. 1, ...
DACE a matlab Kriging toolbox [DB/OL]. (2009-12-21) [2002-08-01]. http://www2.imm.dtu.dk/~hbn/dace. Zitzler E, Deb K, Thiele L. Comparison of multiobjective evolutionary algorithms: Empirical results [J]. Evolutionary Computation, 2000, 8(2): 173–195. Article Google Scholar ...
When using the simulation–optimization model to optimize groundwater extraction-treatment schemes, constructing a surrogate model for the numerical simulation model is an effective tool for overcoming the large computational load. However, the construction of a one-shot static-surrogate model has disadvan...
First, the Optimized Latin Hypercube Sampling (OLHS) algorithm is applied in the Design of Experiment (DOE) to choose representative points. Then sample points are simulated using the CFD method, and the results are exacted to evaluate the objectives of the hydraulic performance. Based on the ...
Furthermore, the implementation of the proposed AOSAOA model is developed by the MATLAB/Simulink platform, and the efficiency of the proposed model is likened to other techniques. Keywords: electric vehicles parking lot; voltage and power loss; atomic orbital search; arithmetic optimization algorithm...
We perform a global sensitivity analysis using the combination of Latin hypercube sampling (LHS) and partial rank correlation coefficient (PRCC) [53,54] to determine the influential parameters of the model as in [55,56,57]. We measure against the increasing number of infected individuals which ...
LHS Latin hypercube sampling WT Wind turbine MILP Mixed integer linear programming WHB Waste heat boiler Variables Parameters t Scheduling time 𝜂𝑙𝑜𝑠𝑠𝑆𝐸𝑆𝑆ηSESSloss/𝜂𝑎𝑏𝑠𝑆𝐸𝑆𝑆ηSESSabs/𝜂𝑟𝑒𝑙𝑒𝑎𝑆𝐸𝑆𝑆ηSESSrelea Self-discharge/charge...