Application of Power System Intelligent Recommendation Algorithm in Improving Human-computer Interactive Experience Model

This study takes intelligent recommendation algorithm in power system as the core, and discusses its application and effect in improving human-computer interaction experience. By combining prior knowledge and expert analysis results, an intelligent recommendation model based on quadratic identification algorithm is designed to improve the efficiency and accuracy of user interaction with the system. The model optimizes user experience by analyzing user behavior data to generate personalized recommendations. In order to verify the effectiveness of the proposed algorithm, system simulation is carried out in this paper. In the simulation process, real power system data is used to test, and the performance of the algorithm in different scenarios is evaluated. Simulation results show that the intelligent recommendation algorithm has improved accuracy and response speed, and can effectively enhance user experience. Especially in the case of combining the expert analysis results, the system’s recommendation effect is more significant. In addition, this paper proves the feasibility and superiority of the proposed algorithm in practical application through accurate data analysis.