Building engineering safety risk assessment and early warning mechanism construction based on distributed machine learning algorithm

Cloud computing has become a hot topic in the industry and academic circles. Large-scale data processing is realized by centralizing system management of network resources, computing resources, and storage resources. Among them, the distributed computing platform greatly improves the productivity of programmers by abstracting the implementation details of distributed computing, and is widely used in building safety assessment. In this study, the construction safety evaluation index system was established for the construction site of common accidents, and the index weight was determined by the analytic hierarchy process. For the safety index evaluation task, an early warning mechanism based on distributed computing and extension theory to build cloud security management is established, which saves the overall calculation time and quantitatively evaluates the security status of the construction site. Finally, the method is verified by engineering examples, and the results show that the method is practical and effective. The method is convenient for computer programming, easy to operate and implement, and has strong applicability. Based on distributed computing and extended cloud model, not only can the overall state of construction safety be judged, but also potential security problems can be identified based on information feedback. The objective existence of hazards in the construction process can be grasped, which has important guiding significance for the construction process.