Safety Warning for Electric Vehicle Charging Utilizing A-LSTM Algorithm

As the adoption of electric vehicles (EVs) continues to surge, ensuring the security of EV charging infrastructure becomes increasingly crucial. This research paper delves into the utilization of Long Short-Term Memory (LSTM) algorithms for the analysis and enhancement of electric vehicle safety. LSTM, a form of recurrent neural network (RNN), proves especially adept at handling time series data—a critical factor in anticipating and averting security issues during the charging process. The article assesses the current state of electric vehicle safety, introduces the LSTM methodology, and presents findings from a study evaluating the efficacy of this approach in predicting and preventing accidents. The results underscore the algorithm's capacity to robustly and reliably identify anomalies, thereby contributing to the overall safety and dependability of electric vehicles.