A Data Mining-based Method for Analyzing and Predicting the Cost of Power Grid Production and Technical Improvement Projects

Due to the diversified characteristics of the factors affecting the cost of the project, the prediction results of the project often have a large error, therefore, we propose a study on the analysis and prediction method of the cost of the grid production technical reform project based on data mining. The composition of the cost of grid production technical reform project and the specific influencing factors are analyzed from the three perspectives of equipment and material cost, labor cost and overhead cost. In the stage of cost prediction, data mining technology is introduced to embed the influencing factors of the cost into the calculation of equipment and material cost, labor cost and overhead cost, so as to obtain more accurate cost prediction results. In the test results, the error between the prediction result of the overall cost of the project and the actual input is only 0.6 million yuan, and the error between the prediction result of various individual costs and the actual input is always stabilized at less than 15,000 yuan.