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

Weiting Chen,Qingdong Wang,Yuming Cai,Lijian Sheng,Jia Lin,Shuanglan Huang,Shaojing Zhuang,Joni Zhong

doi:10.1155/2022/2864208

Weiting Chen, Qingdong Wang + Show 6 more

Open Access

https://doi.org/10.1155/2022/2864208

Copy DOI

Abstract

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.

Highlights

Since the “ irteenth Five-Year Plan,” with the implementation and promotion of policies such as poverty alleviation and rural revitalization, the prominent contradictions in power construction have changed from “utilizing electricity” to “good use of electricity.” e power distribution network is responsible for the distribution of electricity
Data mining technology can deeply dig its value through massive data information and provide strong support for the construction and development of electric power enterprises [5]. erefore, in order to meet the task of power grid construction and lean management and control requirements in the new era, it is urgent to integrate data mining technology into the management and control of distribution network engineering to achieve “digital” management and scientific decision-making [6, 7]
Changes have led to a large gap between budget and actual project investment, sometimes up to 40%, of which government influence factors may account for about 10%

Summary

Introduction

Since the “ irteenth Five-Year Plan,” with the implementation and promotion of policies such as poverty alleviation and rural revitalization, the prominent contradictions in power construction have changed from “utilizing electricity” to “good use of electricity.” e power distribution network is responsible for the distribution of electricity. Erefore, in order to meet the task of power grid construction and lean management and control requirements in the new era, it is urgent to integrate data mining technology into the management and control of distribution network engineering to achieve “digital” management and scientific decision-making [6, 7]. Erefore, it is imperative to integrate data mining technology into the management of the whole process of distribution network construction It is an important cornerstone for the better, stronger, more precise, and more accurate development of the entire process of distribution network management and control [15]. Provide more scientific and accurate support to make the whole process of the project more accurate

Analysis on Influencing Factors of Distribution Network Project Settlement

Data Mining Concepts and Methods

Findings

Project Settlement Forecast of Distribution Network Based on Data Mining