Research On The Application Of Data Mining Algorithms In The Planning And Statistics Of Coal Enterprises

With the continuous development of big data technology,enterprise data informatization has achieved rapid development,and each enterprise is building its own digital management platform.The research group designed and developed the project plan statistical information management system for Yankuang Group.The system has been in operation for many years to realize the information management of the enterprise,the information entry,statistics,analysis,and sorting functions of units and projects.At present,the company has renewed new requirements,hoping to design and develop a big data display subsystem with the help of mature big data mining technology to realize the value of historical data.This paper takes the historical data accumulated by Yankuang Group for many years as the research object,and uses the unsupervised clustering K-means algorithm to classify the project data of Yankuang Group.Obtain the clustering relationship on three project types,seven project adjustment types,six project revenue types,and the overall quality of the project.According to the feature analysis of different types of clustering results,the specific features of each category are obtained.Then,based on the data of the clustering result set,using the Apriori algorithm that introduces the idea of difference,mining the association rules on the basis of the clustering results,and get the strong association rule relationship about the project and the association rule relationship about the comprehensive quality of the project.Provide certain data support for the future development of the group,project approval and decision-making.The Apriori algorithm based on K-means clustering analysis and the introduction of the idea of difference adds a big data display subsystem on the basis of the original Yankuang Group’s planned statistical information management system.The subsystem includes three modules: comprehensive project quality analysis,comprehensive early warning,and precise assistance.Among them,the comprehensive quality analysis of the project is to comprehensively evaluate the quality of the project based on the completed project data;the comprehensive early-warning is the data early-warning of the capital expenditures,project adjustments and project plan application funds in the current implementation projects;precise assistance is for the current implementation Provide reasonable solutions to difficult problems in the project.This subsystem provides reliable data support for Yankuang Group’s project management,project early warning,etc.,which is conducive to improving the company’s revenue efficiency and promoting the precision and scientificization of project management.