Defect Severity Identification for a Catenary System Based on Deep Semantic Learning

. 2022 Dec 16;22(24):9922. doi: 10.3390/s22249922

Algorithm 1 Pseudocode for training the BERT-DTCN.

Require:
$X_{s}$ : training set for the BERT-DTCN, including the constructed defect text dataset and labels; $N_{c}$ : number of classifier-training iterations per mini-batch.
1:
for the number of training iterations do
2:
Sample mini-batch of m examples from the training set $X_{s}$ ;
3:
for $i = 1 \to N_{c}$ do
4:
Update the BERT-DTCN by minimizing the loss: $L o s s_{c}$
5:
end for
6:
end for