Hospital Intelligent Power Operation and Maintenance Information Evaluation with the Long and Short Memory Neural Network

The invention describes a deep learning-based technique for monitoring power grid information operation and maintenance. Based on the time series data information in the power grid information operation and maintenance monitoring system, this method obtains the cleaned time series data through appropriate data preprocessing technology. This also uses the long-term and short-term memory neural network to realize the prediction function of the time series data to be detected. The reason behind is to construct the normal behavior model of the time series. Additionally, the control chart based on an exponentially weighted moving average is employed to determine whether the time series to be discovered contains any anomalous and abnormal phenomena. In the area of power grid information operation and maintenance monitoring, the method of invention is designed to counter anomaly. This phenomenon is universal in nature and has significant scientific importance for guiding treatment after the anomaly is discovered. Additionally, it guards against serious faults that the abnormality might bring about.