Application of Data Mining in the Settlement Management of Distribution Network Projects | Zendy

Weiting Chen | Zendy; Shaojing Zhuang | Zendy; Jia Lin | Zendy; Shuanglan Huang | Zendy; Lijian Sheng | Zendy; Yuming Cai | Zendy; Qingdong Wang | Zendy

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Application of Data Mining in the Settlement Management of Distribution Network Projects

Author(s) -

Weiting Chen,

Shaojing Zhuang,

Jia Lin,

Shuanglan Huang,

Lijian Sheng,

Yuming Cai,

Qingdong Wang

Publication year - 2022

Publication title -

security and communication networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.446

H-Index - 43

eISSN - 1939-0114

pISSN - 1939-0122

DOI - 10.1155/2022/2864208

Subject(s) - computer science , settlement (finance) , investment (military) , process (computing) , transformation (genetics) , distribution (mathematics) , project management , data mining , operations research , systems engineering , biochemistry , chemistry , mathematical analysis , mathematics , politics , world wide web , political science , law , payment , gene , engineering , operating system

With the development of intelligent technology, the distribution network has also ushered in a new round of upgrading and transformation. New technologies, equipment, and platforms will be introduced to bring innovative blood to the distribution network. This paper proposes a data mining settlement management method for distribution network projects. The improved K-means method is used to estimate the coefficients of each link of the project investment. When a large deviation of a certain coefficient is found, the investment adjustment is made immediately to avoid the overall investment. This method can save costs for infrastructure construction, through the data mining deeper, can form a standard, intelligent analysis method, realize based data acquisition to the output results from the application of rapid transformation, realize the material equipment price forecast and project construction cost and fast estimation, provide project decision-making more scientific and accurate, and make the whole process of project cost more accurate.

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