first of all, thanks to the developers who created the nice package.
After creating a data driven PCE model, i want to proceed with robust optimization after extracting the PCE function.
Thus, an m-file was created to solve the toy problem as shown in figure 1. In addition, a total of three input variables were entered and the distribution was input as shown in figure 2.
Thus, a PCE model was created, and the results of the model are shown in Table 1 and Table 2.
Since the coefficient is 0 from the 11th to the 20th, there is no basis for the third order.
What I am trying to do is extract the PCE function and optimize it with MATLAB fmincon.
- The PCE formula was referenced by referring to several papers. I wonder if it is right to expand in the above order(table 3).
0 1 2 3 [1,1] [1,2] [1,3] [2,2] [2,3] [3,3] …
When expand in the above order, it is different from the validation result of the model. Can i extract basis from uqlab package?
X_val = [1.7118, -2.8774, 1.9047] Y_val = [-0.0906], Y_cal = [7.024]
x1 and x2 are Legendre polynomial and x3 is Hermite polynomial. If Legendre and Hermite are multiplied, is it simply to multiply the two polynomials? (table 2. right)
What is the basis of arbitrary PCE? I would like to know if there are related literature.
I would be very grateful with your response.