Researchers are exploring methods for identifying and assessing multiple safety risks that occur when environmental factors interact. Various studies are applying different models and techniques, such as Bayesian criterion-based assessments and fusion of multiple models, to analyze risks in areas like amusement facilities, commercial truck driver behavior, and construction projects. The approaches being investigated include the use of multi-source data, machine learning algorithms, and specific models like the N-K/SNA model to better understand and mitigate complex safety risks.