کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4960082 | 1445969 | 2017 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Regression and Kriging metamodels with their experimental designs in simulation: A review
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Regression and Kriging metamodels with their experimental designs in simulation: A review Regression and Kriging metamodels with their experimental designs in simulation: A review](/preview/png/4960082.png)
چکیده انگلیسی
This article reviews the design and analysis of simulation experiments. It focusses on analysis via two types of metamodel (surrogate. emulator); namely, low-order polynomial regression, and Kriging (or Gaussian process). The metamodel type determines the design of the simulation experiment, which determines the input combinations of the simulation model. For example, a first-order polynomial regression metamodel should use a “resolution-III”design, whereas Kriging may use “Latin hypercube sampling”. More generally, polynomials of first or second order may use resolution III, IV, V, or “central composite” designs. Before applying either regression or Kriging metamodeling, the many inputs of a realistic simulation model can be screened via “sequential bifurcation”. Optimization of the simulated system may use either a sequence of low-order polynomials-known as “response surface methodology” (RSM)-or Kriging models fitted through sequential designs-including “efficient global optimization” (EGO). Finally, “robust”optimization accounts for uncertainty in some simulation inputs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 256, Issue 1, 1 January 2017, Pages 1-16
Journal: European Journal of Operational Research - Volume 256, Issue 1, 1 January 2017, Pages 1-16
نویسندگان
Jack P.C. Kleijnen,