Integration of Artificial Intelligence and BIM in Intelligent Decision Support System for Water Conservancy Projects

A kind of intelligent DSS based on AI and Architecture Information Modeling (BIM) is put forward. The system is composed of several modules, including data collection, processing, intelligence decision-making, feedback and optimizing. The data acquisition and processing module collects environmental data, equipment status and water flow information of water conservancy projects in real time through a variety of sensors and remote sensing technologies; the intelligent decision module uses deep learning algorithms, especially GCN is to model and predict the collected data, so as to make effective risk assessment and scheduling decisions; the feedback and optimization module continuously optimizes the decision process according to real-time feedback information, and improves decision accuracy and response speed. Through a series of experimental simulations, this paper verifies the effectiveness of the system. The GCN-based model improves the forecasting precision by 15% compared with the conventional ANN, and the calculation efficiency is improved 20%. Furthermore, it is proved by experiments that the system has remarkable superiority in dealing with complicated data in real time, data fusion and decision-making.