Risk Control System of Construction Engineering Based on Data Mining and Artificial Intelligence Technology

Abstract

Cloud computing provides a displaying and sharing platform for data mining technology. In order to prevent privacy disclosure, these data often contain artificially added risk control data, which makes the process of data sharing face the problem of deep mining of data. In terms of privacy protection, construction engineering risk control system is usually through the generalization way to complete the sharing of the accurate data, providing a condition for the follow-up accurate query process. At the same time, it also ensures that these data can be effectively predicted. According to the possible intersection or inclusion relationship between the generalized values, the generalized values are stratified and clustered in order to save the related important information of the construction project risk control. On this basis, this paper uses data mining technology (DMT) to design a construction project risk control system (CPRCS) based on data mining technology. Finally, through theoretical analysis and experimental comparison, this paper demonstrates the feasibility and effectiveness of the system.