Research on Diagnosis of Electric Vehicle Charging Data Anomalies Based on BFGO-CNN-LSTM
In order to cope with the negative impact of various perturbations on fault id entification accuracy during electric vehicle(EV)charging,an innovative BFGO-CNN-LSTM model is proposed to accurately diagnose the abnormal parts of EV charging data.In this way,the model is able to fully utilize the spatio-temporal characteristics of EV charging data,which greatly enhances the accuracy and computational efficiency of EV charging data anomaly detection.
data anomaly diagnosisCNNlong and short-term memory neural networkEVoptimization algorithm
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