| In recent years,assembly building has been greatly improved in waste of resources,technological level and construction site.There are many security problems along with development.It is of great significance to ensure the effective control of safety risk of prefabricated building construction.In this paper,BP neural network model is adopted to evaluate the safety of hoisting operation.BP neural network evaluation model is not linear but nonlinear.This is an innovation that brings a new evaluation data processing model,which will make the results of risk assessment accurate.In this paper,the core hoisting operation of assembly building is studied.First,related research and development status at home and abroad are summarized.Based on this,safety risk factors are analyzed and an evaluation index system is established.The weight of each input index is calculated through the analytic hierarchy process,and the expert’s score is provided with the reference of heinrich accident principle,so as to make the input index value more accurate and authentic.The risk evaluation model of the assembling operation of BP network was established through the neural network training by the software MATLAB2016a.The evaluation model of BP neural network can deal with non-linear problems,which is also the main reason for adopting BP neural network for risk evaluation in this paper.Through BP neural network evaluation model,we can directly see the risk point of assembly building hoisting operation,and can provide a good reference for future construction.In addition,based on the BP neural network evaluation model,the qualitative control measures for related risk points were proposed,and the qualitative and quantitative methods were adopted.From the perspective of whether there is cross operation,the corresponding cross operation control model is established to carry out quantitative optimization control of the risk of lifting operation in prefabricated buildings. |
PDF Full Text Request