Algorithm 1 The regional surrogate model technique.

Input: the number of initial samples N; the parameter space $PS$; the criteria of the SOS. Output: A classifier; a regional SUMO  Definition: the selected training set for the SUMO $ST$; the training set for classifier $CT$ 1: Make the initial sample selection from the $PS$ and get N samples 2: Put selected samples into the simulation model to get their response 3: for each sample and its response 4:  if i-th sample belongs to the SOS 5:   add i-th sample and its response into $ST$; 6:   classify i-th sample with class 1; 7:   add i-th sample and its class into $CT$; 8:  else 9:    classify i-th sample with class 0; 10:   add i-th sample and its class into $CT$ 11:  end if 12: end for 13: Train the SUMO by $ST$ 14: Train the classifier by $CT$