Big Data Mining and Prediction Model in Building Economic Analysis

This paper focuses on the research of big data mining and prediction model in building economic analysis. This paper proposes a building economy analysis method based on big data mining technology, and innovatively introduces Sparrow Search optimization (SSO) algorithm to optimize the support vector regression (SVR) model. This method first extracts key features from massive building economic data through big data mining technology, and then uses sparrow foraging behavior heuristic algorithm to efficiently optimize SVR model parameters, thereby building a high-precision building economic prediction model. This paper also develops a building economic information monitoring system, which can automatically collect, process, and analyze the building economic data, and display the analysis results through a visual interface. In order to verify the validity and feasibility of the proposed method, a detailed model simulation experiment is carried out in this paper. The experimental results show that compared with traditional big data mining and prediction methods, the proposed building economic analysis method based on sparrow search optimization SVR model has better performance in terms of prediction accuracy and stability.