Research on Safety Analysis and Prediction Technology for Crane Operation Based on Intelligent Algorithms

In recent years, with the rapid development of China’s construction industry, various safety accidents caused by it have occurred frequently, causing huge losses to people’s lives and property. In order to reduce the probability of crane accidents, the advantages of intelligent algorithms were applied to stratify and decompose the causes of accidents, and identify key triggers. By utilizing deep learning and data mining techniques, combined with crane operation data and accident cases, a safety analysis model based on neural networks was established, and this model was used for accident risk prediction and warning. In the data validation of real crane construction sites, the model has shown high accuracy and effectiveness. The research results indicated that intelligent algorithms had significant effects in crane safety management. The crane safety prediction model established based on this method had good prediction ability for disasters such as collapse and high-altitude falls, with recall rates of up to 0.95 and 1, and accuracy in predicting comprehensive accidents of 0.884. Overall, it is in a good state. The research results of this article can provide new ideas and approaches for the study of safety control issues during on-site construction, and provide new methods for improving safety during the construction process.