It is an effective means to improve urban operational safety and risk response capabilities by analyzing urban operation-al safety monitoring data,identifying urban operational risks and proposing targeted risk control.In this paper,it uses machine learn-ing unsupervised learning clustering algorithm and statistical analysis method,combined with big data mining technology,to establish an algorithm model of urban operation safety monitoring to objectively reflect the state of urban operation safety.Based on the research results,a typical city in China is selected as an example application verification,and the algorithm model designed in this research has been verified through practice to fully explain the city's security status and hidden problems.The research results of this paper establish an algorithm model foundation for the monitoring of urban operation safety status and identification of safety risks,and pro-vide reference and basis for relevant application practices.
关键词
智慧城市/机器学习/数据挖掘/算法模型
Key words
smart city/machine learning/data mining/algorithm model
维普
万方数据