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基于机器学习的变电站火灾风险评估与预警模型开发

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提出了一种基于机器学习的火灾风险评估与预警模型,以实时监控和预警潜在风险.分析了火灾风险源,识别了关键因素并探讨了量化评估方法.介绍了机器学习算法选择、优化及模型构建过程,包括数据预处理和特征提取.同时,设计了火灾预警系统,实现了直观监控和及时预警,以期为变电站安全管理提供新思路和方法.
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.

substationfire risk assessmentmachine learningearly warning systemsafety management

张国瑞、郭琦、吴涛、何方明、刘涛

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国网北京通州供电公司,北京 100000

变电站 火灾风险评估 机器学习 预警系统 安全管理

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(19)