首页|基于机器学习算法的智慧城市运行安全监测模型研究

基于机器学习算法的智慧城市运行安全监测模型研究

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对城市运行安全监测数据进行分析,识别城市运行风险并有针对性地提出风险管控措施,是提高城市运行安全水平和风险应对能力的有效手段.利用机器学习非监督学习聚类算法和统计分析方法,结合大数据挖掘技术,建立城市运行安全监测算法模型,反映城市运行安全状态.基于研究结果,选择国内某典型城市开展实例应用验证,通过实践验证了此次研究设计的算法模型能充分说明了城市安全状态和问题隐患.研究成果为城市运行安全状态监测、安全风险的识别建立了算法模型基础,为相关应用实践提供了参考和依据.
Research on Model of Smart City Operation Safety Monitoring Based on Machine Learning Algorithm
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.

smart citymachine learningdata miningalgorithm model

曾莎洁

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上海市建筑科学研究院有限公司,上海 200032

上海市工程结构安全重点实验室,上海 200032

智慧城市 机器学习 数据挖掘 算法模型

上海市"科技创新行动计划"社会发展科技攻关项目

22dz1201500

2024

自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
年,卷(期):2024.(7)