TY - JOUR
ID - 521783
TI - APPLICATION OF KRIGING METHOD IN SURROGATE MANAGEMENT FRAMEWORK FOR OPTIMIZATION PROBLEMS
JO - International Journal of Mathematical Modelling & Computations
JA - IJM2C
LA - en
SN - 2228-6225
AU - Azarkhalili, B.
AU - Rasouli, M.
AU - Moghadas, P.
AU - Mehri, B.
AD - Sharif University of Technology, Azadi Ave, Tehran, Iran
Iran, Islamic Republic of
Mathematics Department
AD - Sharif University of Technology, Azadi Ave, Tehran, Iran
Iran, Islamic Republic of
Electrical Engineering Department
AD - Sharif University of Technology, Azadi Ave, Tehran, Iran
Iran, Islamic Republic of
Aerospace Engineering Department
AD - Sharif University of Technology, Azadi Ave, Tehran, Iran
Department of Mathematics
Y1 - 2012
PY - 2012
VL - 2
IS - 1 (WINTER)
SP - 35
EP - 44
KW - Surrogate Management Framework
KW - Kriging
KW - Computational Order
KW - convergence
KW - Gradient
DO -
N2 - In this paper, Kriging has been chosen as the method for surrogate construction. The basic idea behind Kriging is to use a weighted linear combination of known function values to predict a function value at a place where it is not known. Kriging attempts to determine the best combination of weights in order to minimize the error in the estimated function value. Because the actual function value is not known, the error is modeled using probability theory and then minimized. The result is a linear system of equations that can be solved to ﬁnd a unique combination of weights for a given point at which interpolation is to be performed.
UR - http://ijm2c.iauctb.ac.ir/article_521783.html
L1 - http://ijm2c.iauctb.ac.ir/article_521783_2dcfc23cecf6d197cca235f2805c8bff.pdf
ER -