Open access
Aug 2026
Enhancing Intelligent Fault Detection and Classification in Power Grid Engineering Using LSTM Neural Networks
The findings show that the suggested hybrid model works better than conventional techniques, with a fault classification accuracy of 98.66% as opposed to decision trees’ 97.42% and SE-CDAE’s 97.98% accuracy.
Qinghua Chen, Tao Xu, Cheng Zhou et al.
· Distributed Generation &... · 0 citations