An efficient response surface method using moving least squares approximation for structural reliability analysis

By Soo-Chang Kang, H. Koh, J. Choo. 2010

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LIF: A new Kriging based learning function and its application to structural reliability analysis (2017, background): “Considering an analytical example with 2-dimension input variable [15,20,45], its performance function is ( ) = ( + ) − ( + ) − ( ) x G x x exp 0.”
Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment (2017, background): “The local MLS approximation at x is formulated as [20] ~Lðx; xiÞ ¼ bðxiÞTaðxÞ ð65Þ where xi denotes experimental points and the basis functions BðxÞ are commonly chosen as bðxÞ ¼ 1x1 . . . xnx2 . . . x2n T ð66Þ The vector of unknown coefficients aðxÞ is determined by minimizing the error between the”
A new adaptive response surface method for reliability analysis (2013, methodology): “[26] use moving least square method but the size of additional ED around the design point is empirically chosen.”