Fault prediction model based on PSO–LSTM–ATT

Abstract Aiming at the problem of low fault prediction accuracy of new energy cables, a fault prediction model based on PSO–LSTM–ATT is proposed. First, a random forest-based cable fault feature screening model is proposed to screen important features and establish a cable fault feature parameter system. Then, a modified PSO–LSTM–ATT prediction model is used to calculate the residual difference between the predicted value and the actual value, and the running status of the new energy cable is determined according to the residual distribution. Experimental results show that the prediction accuracy reached 92.9%.