Application of Machine Learning Algorithm in Stadium Engineering Building Information Model Management System

Abstract

BIM (building information modeling) is a building information modeling technology. It is a modeling technology that has quietly emerged in the architectural design and construction industry and will gradually replace the traditional CAD drawing technology. In addition to carrying geometric information of graphics, it can also carry buildings and building components. The engineering and nonengineering information of the building space has a higher degree of visualization and a stronger sense of three-dimensionality, and all the building information can be put into a model. The model can provide dynamic information on engineering construction cost management processes and can be processed by a computer in real time. The purpose of this paper is to study the new method of stadium project building information model management after the introduction of deep learning technology. This article first introduces the artificial neural network under machine learning algorithms by building a neural network model and combining it with the engineering construction information model and then integrating machine learning algorithms into the construction information model technology so that the originally three-dimensional model can further information integration. Compared with the original building information model, the data processing is more efficient and the management level has greatly improved. The experimental results of this paper show that machine learning algorithms can optimize the construction information model of stadium engineering and increase the efficiency of project management by 20%.