Deep learning-based power outage impact on users and power outage loss analysis

This paper proposes a method for analyzing the impact of power outages on users and predicting losses based on deep learning. By processing heterogeneous data from multiple sources, a high-quality dataset is constructed, and algorithms such as MLP, Random Forest, and SVR are used to train models for user classification and loss prediction. Based on this, a comprehensive analysis system integrating data management, model analysis, and visualization display is designed and implemented. Through testing, the system's usability, stability, and security are verified. This research provides a datadriven analysis tool for power companies and government decision-making departments, with important theoretical and practical significance.