Development of Substation Fire Risk Assessment and Early Warning Model Based on Machine Learning
Propose a machine learning-based fire risk assessment and early warning model for real-time monitoring and warning of potential risks.Analyzed the sources of fire risk,identified key factors,and explored quantitative evaluation methods.Introduced the process of machine learning algorithm selection,optimization,and model construction,including data preprocessing and feature extraction.At the same time,a fire warning system has been designed to achieve intuitive monitoring and timely warning,in order to provide new ideas and methods for the safety management of substations.