Tower Crane Operational Risk Level Assessment Based on Improved Evidence Theory

This study proposes a tower crane operational risk level assessment method based on an improved evidence theory. This approach integrates the capability of the improved evidence theory to handle uncertainty and the advantages of cloud modeling in addressing fuzziness, aiming to enhance the accuracy and reliability of the assessment. Firstly, by constructing a trust network, factors related to tower crane operation are represented as nodes, and the trust distribution of nodes is transformed into cloud models using the improved evidence theory. Secondly, various items of evidence are collected and represented as cloud evidence. The final cloud models for each node and edge are synthesized using the operational rules of cloud models, considering the uncertainty of different evidence and weights. Finally, the synthesized cloud models are employed for tower crane operational risk level assessment, allowing flexibility to adapt to changes in dynamic environments. This method provides decision-makers with more comprehensive, reliable, and interpretable information regarding tower crane operational risk levels, offering robust support for safety management and decision-making. In practical applications, adjustments to model parameters and weights should be made based on real-world conditions and domain expertise to ensure the effectiveness of the assessment results.