Risk index evaluation of prefabricated buildings based on Monte Carlo and visual recognition neural network

Abstract

Abstract Based on the analysis of the risk occurrence path of prefabricated buildings, this paper identifies the key factors of construction risk, expounds the risk occurrence mechanism of construction, and builds a risk assessment model of construction based on Monte Carlo visual recognition neural network. At present, with the rapid development of social economy, various materials have been excavated and put into use in the field of construction. In addition contemporary problems with materials pollution have become increasingly prominent, especially in the construction industry. People have begun to pursue a more comfortable and environmentally friendly housing environment. Prefabricated buildings have their unique advantages in the modernization of such a construction industry. developed against the background. Due to the change in the construction mode, the quality of design and construction personnel, as well as the existing technical capabilities and supporting facilities have not reached the due level, and the resulting safety problems need to be solved urgently. There are many risk factors in the implementation process, and the risks The probability and consequences are difficult to accurately judge. In this paper, through the identification of risks in prefabricated building projects, a risk index evaluation system is established, and the risk of prefabricated buildings is evaluated and studied risk evaluation, the influence of human subjectivity can be overcome, and the evaluation results can be It is more accurate and reasonable, and finally achieves the purpose of risk management and control, and puts forward corresponding measures according to the evaluation results, which provides new ideas and methods for the risk assessment and model optimization research of prefabricated buildings.