Research on High-precision Automation Control of Transformers Based on Arti-ficial Intelligence
A high-precision automatic control algorithm for transformers based on artificial intelligence is designed to address the issues of insufficient control accuracy in existing power equipment control algorithms.Firstly,collect oper-ational data related to the working status of transformers based on sensors as input data for the CNN network model.Secondly,based on the global retrieval function of the GWO algorithm,the optimal CNN network parameters are se-lected,and the ReLU function is used as the activation function for the convolutional layer to reduce the gradient di-lation problem of the convolutional layer.Finally,the training error is synchronously controlled in the output layer of the fully connected layer to improve the final control effect.The experimental results show that the artificial intelli-gence CNN control algorithm has an accuracy of 98.6％and 98.3％in identifying abnormal data in the training and testing sets.
artificial intelligencehigh precision transformerCNNautomation controlactivation function
万方数据
维普
