Model Design for Prediction and Evaluation of Transmission Engineering Data Based on Hybrid Convolutional Network Algorithm

This study designed a new data prediction and evaluation model based on hybrid convolutional network algorithm, and used evaluation models such as mean square error (MSE), mean absolute error (MAE), and accuracy. The experimental results showed that the model had low MSE and MAE, as well as an accuracy of 83.3%. This shows that the proposed model is able to capture the trend of data of PTTP precisely, which provides a strong support for the stability and performance assessment of the power system. This method has not only improved the accuracy of data prediction, but also contributed to the reliability and performance evaluation of power engineering.