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Neural Network-Driven Fault Classification for HVAC Transmission Systems: A Comparative Evaluation of Voltage, Current, and Phase Angle Inputs

The results indicate that phase-angle information provides supplementary and class dependent discriminative value, but does not consistently improve all fault classes, whereas conventional voltage and current measurements alone represent a simpler and more stable alternative, whereas phase-angle measurements may be incorporated when synchronized phasor information is already available.