Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm
In order to effectively control the cost risk of power grid construction projects, the author proposes a cost risk management system for power grid construction projects based on the fuzzy clustering algorithm. The system introduces the fuzzy clustering maximum tree algorithm, and by constructing a...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/9328038 |
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| author | Ping Zhong Hang Yin Yuanfu Li |
| author_facet | Ping Zhong Hang Yin Yuanfu Li |
| author_sort | Ping Zhong |
| collection | DOAJ |
| description | In order to effectively control the cost risk of power grid construction projects, the author proposes a cost risk management system for power grid construction projects based on the fuzzy clustering algorithm. The system introduces the fuzzy clustering maximum tree algorithm, and by constructing a mathematical model, combined with the empirical analysis, the key risk factors in the cost risk of power grid construction projects are identified. Through the analysis, it can be concluded that the key risks in the cost risk of power grid construction projects are the planning risks of infrastructure projects, the research risks of infrastructure projects, and the cost risks of infrastructure projects. Experimental results show that combined with expert experience and the actual situation of power grid engineering, the classification result at threshold λ=0.785 becomes more realistic. At this λ level, 6 risk factors are grouped into 4 categories as follows: class I x1,x2,x4, class II x3, class III x5, and class IV x6. Through research, the identification of key risks can enable project managers to control the cost of power grid construction projects, targeted, so that risks can be minimized and investment returns can be improved. |
| format | Article |
| id | doaj-art-65f450b5b3034bd7908b28074b87dd0f |
| institution | Kabale University |
| issn | 1687-5257 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-65f450b5b3034bd7908b28074b87dd0f2025-02-03T01:32:28ZengWileyJournal of Control Science and Engineering1687-52572022-01-01202210.1155/2022/9328038Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering AlgorithmPing Zhong0Hang Yin1Yuanfu Li2School of Civil EngineeringBusiness SchoolSchool of Civil EngineeringIn order to effectively control the cost risk of power grid construction projects, the author proposes a cost risk management system for power grid construction projects based on the fuzzy clustering algorithm. The system introduces the fuzzy clustering maximum tree algorithm, and by constructing a mathematical model, combined with the empirical analysis, the key risk factors in the cost risk of power grid construction projects are identified. Through the analysis, it can be concluded that the key risks in the cost risk of power grid construction projects are the planning risks of infrastructure projects, the research risks of infrastructure projects, and the cost risks of infrastructure projects. Experimental results show that combined with expert experience and the actual situation of power grid engineering, the classification result at threshold λ=0.785 becomes more realistic. At this λ level, 6 risk factors are grouped into 4 categories as follows: class I x1,x2,x4, class II x3, class III x5, and class IV x6. Through research, the identification of key risks can enable project managers to control the cost of power grid construction projects, targeted, so that risks can be minimized and investment returns can be improved.http://dx.doi.org/10.1155/2022/9328038 |
| spellingShingle | Ping Zhong Hang Yin Yuanfu Li Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm Journal of Control Science and Engineering |
| title | Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm |
| title_full | Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm |
| title_fullStr | Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm |
| title_full_unstemmed | Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm |
| title_short | Analysis and Design of the Project Risk Management System Based on the Fuzzy Clustering Algorithm |
| title_sort | analysis and design of the project risk management system based on the fuzzy clustering algorithm |
| url | http://dx.doi.org/10.1155/2022/9328038 |
| work_keys_str_mv | AT pingzhong analysisanddesignoftheprojectriskmanagementsystembasedonthefuzzyclusteringalgorithm AT hangyin analysisanddesignoftheprojectriskmanagementsystembasedonthefuzzyclusteringalgorithm AT yuanfuli analysisanddesignoftheprojectriskmanagementsystembasedonthefuzzyclusteringalgorithm |