# Security Situation Assessment for Terminal Area Control System Operation Based on BN-ISSA-ELM
## 5 Conclusions  
This study differentiates itself from other methodologies that depend exclusively on individual risk source identification by integrating both active and passive risk identification strategies. This thorough methodology facilitates the identification of safety-related components within the terminal area control system and develops an indicator system appropriate for evaluating the operational safety status of the terminal area control system. Two tiers categorize the evaluation of operational risks in the terminal area control system, resulting in the development of a primary indicator prediction model and a safety situation assessment model based on the ISSA-ELM framework. An experiment shows that the 19 secondary indicators found for the safety status of the terminal area are in line with the three main dangerous events, showing a mapping link. The enhanced Extreme Learning Machine proficiently delineates this relationship and reliably forecasts the operational risks linked to the terminal area control system, attaining a prediction accuracy exceeding 80% post-optimization. Moreover, comparisons between the model's evaluation outcomes and the actual operational conditions of the terminal area during the same period demonstrate consistent results. This suggests that the suggested method may consistently evaluate the operational safety status of the terminal area control system, offering critical insights for safety management staff to make educated decisions. This research positively contributes to the study of safety situational awareness in terminal area control systems. The BN-ISSA-ELM terminal area control system operation safety situation assessment model established in this paper integrates the uncertainty inference capability of the BN, the efficient optimization performance of the ISSA, and the fast learning and generalization characteristics of the ELM. In practical applications, the model can firstly predict the occurrence probability of typical unsafe events caused by various complex factors and their interactions, such as a sudden change in air traffic flow, the deterioration of meteorological conditions, and hidden equipment failures. Secondly, based on the model's accurate assessment of the safety situation, it can provide a scientific basis for the rational allocation of resources. For example, in practical application, when the model predicts that a high safety risk will occur in a certain area, it can prompt the control department to deploy experienced controllers to key positions in a timely manner to strengthen the monitoring and command of key flights. The model can also be used to simulate and evaluate various response options under different security situations, helping controllers to choose the optimal decision to reduce the expansion of security risks due to decision-making errors or hesitation. At the same time, the model can continue to evaluate the changes in the security situation during the emergency response process, providing real-time information  
Figure 9: Security situation of the terminal area control system operation. for adjusting the emergency response strategy to ensure the effectiveness and adaptability of the emergency response. The long-term application of the BN-ISSA-ELM model to assess the security posture of the terminal area control system helps to identify the potential weaknesses and security risks in the system, and provides direction for the continuous optimization of the system. Through the in-depth analysis of a large amount of assessment data, frequent risk patterns in airspace areas or time periods can be identified, which can then be targeted for the improvement and optimization of the control process, equipment configuration, personnel training, and other aspects.