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Accuracy

What is the approximation error of the result?

The approximation error indicators (predict the metamodel accuracy of the results) can be either visualized in the LS-OPT Viewer  or found in the lsopt_output file, e.g. for the response HIC you may find:

 

LS-OPT Viewer

 

Start the LS-OPT Viewer by selecting the View tab and

  1. Select under Metamodel the item Accuracy
  2. From Entity select Responses → HIC.
  3. We can find RMS Error and R2 (R-sq) above the plot.

 

 

 

 

 

 

 

 

 

→ The coefficient of determination (R2) is high (=0.922), but the RMS Error may need further improvement, e.g. more iterations or selection of a more suitable metamodel (e.g. Feedforward Neural Network or Radial Basis Function Network). Nevertheless for a raw estimate the result may be considered as acceptable.

new_plot1.png

acc_responses_view1.png

lsopt_output File

 

  1. Open the lsopt_output file with a text editor.
  2. Search in the file for "Approximating".
  3. Find the appropriate values for root mean square error (RMS Error) and R2.
acc_responses_file1.png

 

With the same procedure you may find the RMS Error and R2 of the other responses:

 

Mean Response Value

RMS Error

R2

MASS

0.7742

0

1

Disp1

-159.3846

2.0286 (1.27%)

0.4790

Disp2

-694.5753

5.5459 (0.80%)

0.9896

HIC

275.72

76.5620 (27.77%)

0.9224