The Evaluation For Builders Hoist Safety Based On GA-BP Neural Network

As a kind of familiar transport machinery in the building work, builders hoist is becoming used much more widely with an increasing number of high-rise buildings in our country. A safety evaluation on builders hoist should be made, due to the fact that many factors threat to the safety of construction during use. This dissertation devoted to solving the problem of subjective evaluation methods, inaccurate and evaluation indicators in available safety evaluation of builders hoist is summarized as follows:Firstly, the reason of builders hoist accidents is analyzed by combining the Accident-causing theory and man-machine-environment system engineering theory with structural characteristics of builders hoist to summarize the three unsafe factors from human, builders hoist and environment.Secondly, the goal of the safety assessment system of builders hoist is established, and factor sets are made based on the relevant regulations and standards and the reason analysis of builders hoist accidents. The safety assessment system is built based on the research, we make the evaluation table of the builders hoist.Thirdly, by considering the advantages of the BP neural network and that of the genetic algorithm, one can build the model of the safety evaluation on builders hoist based on GA-BP network by adopting the genetic algorithm to optimize the weights of the BP neural network.Finally, according to the real example, the safety assessment results of builders hoist based on GA-BP neural network verify the reliability and accuracy of the proposed method. Therefore, the good evaluation result and the practical value could be obtained by applying the GA-BP neural network technology to the safety evaluation.