Price classification prediction of substation reconstruction and expansion engineering equipment based on cluster analysis and regression algorithm

In the substation reconstruction and expansion project, equipment price prediction is a key link to ensure the rationality of budget and cost control. In this paper, a classification and prediction method of equipment price combining cluster analysis and regression algorithm is proposed. In this paper, cluster analysis is used to classify equipment, and then the price fluctuation law of different types of equipment is identified, and then the regression model is used to predict various types of equipment. After experimental analysis, the constructed prediction model has a high accuracy in the price prediction of equipment. According to the experimental results, the method based on cluster analysis and regression algorithm constructed in this paper can reasonably predict the price of transformer equipment, among which, the R² value of the regression model is 0.92, the fluctuation range of the prediction results is 280,000 yuan to 60,000 yuan, the price fluctuation range of the control system is 210,000 yuan to 30,000 yuan, and the R² value of the regression model is 0.94, which has excellent prediction accuracy. The final experiment shows that this method can effectively improve the accuracy of equipment price prediction, which can help the project team to adjust the procurement budget reasonably, avoid the risk of capital waste and insufficient supply, and provide better support for the smooth implementation of the project.