Application of machine learning-based BIM in green public building design

Public activities are mostly carried out in large public buildings, which are closely related to social management. At present, people’s demand for public building facilities is increasing, its shape evolution is becoming more complex, and the scientific and technological content of construction-related technology is also increasing. The development trend of green public buildings is more and more strong. The traditional building design cannot effectively deal with the energy consumption of public buildings and people’s demand for their performance. This paper introduces BIM and machine learning technology to study their practical application in the design of green public buildings and tests the perfect machine learning algorithm. According to the experimental test results, the building energy consumption decreased by 14.3%, the carbon emission decreased by 11.39%, and the absolute value of PMV thermal comfort decreased by 34.7%, which obviously achieved the optimization effect. BIM technology parametric design can enable the design model formed by conceptual design research to automatically draw construction drawings, detailed drawings and other drawings according to the drawing requirements and standards, thus saving the designer's time and enabling him to transfer the drawing time to the program design. Finally, through experiments, the economy, rationality and operability of using BIM technology to design green public buildings are confirmed. In this paper, machine learning and BIM technology are introduced, so as to carry out design research for green public building design.