| 机器学习算法下水利工程风险因素关系分析 |
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| 引用本文： | 孙开畅,冯继伟. 机器学习算法下水利工程风险因素关系分析[J]. 水力发电, 2022, 48(1): 91-93,117. DOI: 10.3969/j.issn.0559-9342.2022.01.016 |
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| 作者姓名： | 孙开畅 冯继伟 |
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| 作者单位： | 三峡大学水利与环境学院,湖北 宜昌443002 |
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| 基金项目： | 国家重点研发计划资助项目(2017YFC0805100)。 |
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| 摘 要： | 为了加强水利工程事故风险管理和预防事故发生,引入了机器学习中的数据关联算法,对水利工程事故案例的风险因素进行多维关联分析。在经过改进的人为因素与分类系统(HFACS)的水利工程风险框架体系的基础上,采用机器学习中的Apriori关联算法对事故案例中的风险因素进行数据挖掘,计算事故风险因素之间的多维关联规则,进而对事故案例的关键影响因素进行识别和分析,并为应急管理及应急救援提供数据分析及技术保障。
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| 关 键 词： | 机器学习 Apriori算法 数据挖掘 多维关联 水利工程 |
Analysis of Risk Relationship of Water Conservancy Projects Based on Machine Learning Algorithms |
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| SUN Kaichang,FENG Jiwei. Analysis of Risk Relationship of Water Conservancy Projects Based on Machine Learning Algorithms[J]. Water Power, 2022, 48(1): 91-93,117. DOI: 10.3969/j.issn.0559-9342.2022.01.016 |
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| Authors: | SUN Kaichang FENG Jiwei |
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| Affiliation: | (School of Hydraulic&Environmental Engineering,China Three Gorges University,Yichang 443002,Hubei,China) |
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| Abstract: | In order to strengthen the risk management of water conservancy engineering accidents and prevent accidents,the data association algorithm in machine learning is introduced to conduct multi-dimensional association analysis on the risk factors of water conservancy engineering accident cases.On the basis of the establishment of water conservancy project risk framework system based on the improved human factors and classification system(HFACS),the Apriori correlation algorithm in machine learning is used to conduct data mining on the risk factors in accident cases and the multi-dimensional correlation rules between accident risk factors are calculated.Further,the key influencing factors of accident cases are identified and analyze,that provides data analysis and technical support for emergency management and emergency rescue. |
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| Keywords: | machine learning Apriori algorithm data mining multi-dimensional association water conservancy project |
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