Search

Neural networks have received a lot of attention in recent years. However, neural networks are rarely used in the construction industry, especially for the risk assessment of new projects such as green buildings. This paper was mainly based on the theoretical analysis of green building evaluation and the establishment of green building comprehensive evaluation index system. Based on artificial neural network, the comprehensive evaluation system of green building projects has been studied. According to the principle of construction risk evaluation index system, a risk evaluation index system corresponding to green building projects has been established. According to the established risk index system, the corresponding BP (back propagation) neural network model was constructed. The BP neural network was learned and trained by MATLAB (matrix&laboratory) software. BIM (Building Information Modeling) model can carry the characteristics of building parameters and the characteristics of BIM technology collaborative design, information interoperability, performance simulation and other characteristics were used. Based on the information transfer between Autodesk’s Revit software and other analysis software, with DB-Link (Database Link) plug-in, Access database, Excel functions and macro commands as the medium, a green building auxiliary evaluation module based on BIM technology was constructed. According to the established comprehensive evaluation index system, the software and neural network model were used to conduct a comprehensive evaluation of green buildings for a green complex building project. The utilization rate of recyclable materials in the architectural design scheme of this project accounted for 17.66% of the total building materials. The results of the evaluation show that a green comprehensive building project has been built in a good grade, which is in line with its actual situation in the green building grade.