Risk Assessment on High-risk Operation in Hydropower Projects Based on Multivariate Connection Number
In order to analyze the risk status and change trend of high-risk operation in hydropower projects,considering the complexity and uncertainty of the evaluation system,this paper proposes a five element connection number analysis method for risk assessment of high-risk operation in hydropower project...
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| Main Author: | |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Pearl River
2021-01-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2021.06.018 |
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| Summary: | In order to analyze the risk status and change trend of high-risk operation in hydropower projects,considering the complexity and uncertainty of the evaluation system,this paper proposes a five element connection number analysis method for risk assessment of high-risk operation in hydropower projects based on the five element connection number set pair analysis theory,constructs an index system,which covers four types of first-class risk indicators and 20 second-class risk indicators,including enterprise influence,safety management,construction personnel behavior and site operation according to the construction characteristics of hydropower projects,expands the connection number of set pair analysis and sets the weight of evaluation index by entropy method and order relation analysis method,establishes an identical discrepancy contrary (IDC) assessment model for high-risk operation in hydropower projects,predicts and analyzes the risk status and change trend through situation function and full & partial connection number,and assesses the risk status of high-risk operation taking a hydropower project as an example.The research shows that the high-risk operation in the hydropower project is low risk,and the system shows a negative development trend,which provide a theoretical basis for risk management and control of high-risk operation in hydropower projects. |
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| ISSN: | 1001-9235 |