This project developed a 4/5G network performance improvement platform based on scene intelligence, which intelligently adjusts the wireless environment of the entire network through the use of big data analysis, IT automation, AI, digital twin and other technologies.This project can evaluate the quality of the wireless environment based on different scene characteristics, match the scene to which the environment to be improved belongs and the high-quality reference environment under the same scene, and optimize the configuration scheme of the target environment based on the configuration scheme of the reference environment to achieve a communication-side full-scene wireless network optimization digital solution. The innovation of this project lies in using digital twin technology, the real-time status and performance data of physical wireless networks are mapped into virtual network models to achieve high-fidelity simulation and prediction of wireless networks, providing a more accurate decision-making basis and more efficient execution schemes for network optimization. Using deep reinforcement learning and large model technologies to identify network status changes, make decisions on base station configuration parameter adjustment, control execution in zero-touch, and optimize multiple objectives of the network in hours or even in minutes. Platform for Improving 4/5G Network Performance Based on Scene Intelligence, integrating frontline expert experience and a massive case database. It addresses technical barriers such as equipment model limitations and data model differences. Innovatively, it introduces digital twin technology to overcome challenges and achieve bidirectional collaboration and prediction between the live network environment and virtual models. Ultimately, it establishes an intelligent, all-scenario wireless network optimization digital solution. This solution or platform has been deployed in over twenty provinces, including Beijing, Henan, and Shandong. Future plans involve nationwide promotion in China, aiming to achieve minute-level automatic optimization of wireless network parameters across all scenarios, with no manual network parameter strategy development. This will enhance user-perceived network metrics by more than 5%, significantly promoting network quality and intelligence, ultimately achieving cost reduction and efficiency improvement goals.