# Security Situation Assessment for Terminal Area Control System Operation Based on BN-ISSA-ELM
## 1 Introduction  
The official organization of civil aviation of China released the Civil Aviation Industry Development Statistical Bulletin, which shows that the safety performance of civil aviation in 2023 remained stable and under control, with the rolling ten-year major accident rate for commercial aviation at 0.0249 per million flights. However, in contrast to favorable safety trends, China's civil aviation traffic volume continues to grow steadily, placing greater pressure on air traffic control (ATC) systems. The terminal area control system, as a critical subsystem of ATC, is characterized by high traffic complexity and rapid situational changes, and many unsafe events are concentrated in this area. Despite this, research on the short-term evolution of safety situations in terminal area control systems remains limited. Therefore, assessing the operational safety level of terminal areas as a system is highly beneficial for ensuring safe operations. Situational awareness, which first emerged from human factors research in aerospace operations [1], gives rise to the concept of security situations, which have found widespread application in fields such as cybersecurity [2]. As the methods for safety situation assessment have developed, some scholars have extended their application to other fields. [PERSON] [3] constructed a safety situation assessment model for civil aviation by selecting key influencing factors and combining Elman neural networks and BP neural networks. In 2015, [PERSON] et al. built a situation prediction model that combined wavelet theory and neural networks for analyzing and forecasting air traffic management network security [4]. [PERSON] et al. introduced a method for identifying flight safety situations based on complex network theory [5]. [PERSON] et al. developed an indicator system for assessingthe safety situation in complex low-altitude flights and identified key safety indicators through simulation experiments [6]. More recently, in 2023, [PERSON] et al. proposed a model for evaluating the operational safety of air traffic control in small- and medium-sized airports based on a variable-weight matter-element extension model [7]. In conclusion, despite the introduction of safety situation research into civil aviation, there are still few studies that concentrate on the operational safety situation of terminal area control systems. Thus far, most studies on these systems concentrate on \"risk assessment\" [8; 9], examining various aspects or specific scenarios of terminal area operations and the associated dangers [10; 11]. In 2016, [PERSON] et al. [12] proposed a fuzzy theory-based FMEA analysis method for the risk assessment process of airport runway systems, but they did not extend the method to larger systems. In 2018, [PERSON] [13] used a process-based FMEA to identify the potential risk factors of the terminal area control system, but their subsequent assessment method still used conventional mathematical models. In 2023, [PERSON] [14] used the 2-4 model to identify the risk elements of the terminal area control system, and his subsequent assessment method also used a mathematical model. The use of only a single risk source identification method does not ensure the comprehensiveness of element identification, while the speed of the mathematical model's assessment method may be flawed when faced with huge computational demands. Furthermore, using cutting-edge technologies to evaluate the complexity of air traffic conditions is the way of the future for air traffic management, as it moves into an era of intelligent development. This study presents a model for evaluating the operational safety situation for terminal area control systems. The goal of the model is to provide a thorough explanation of the variables that affect terminal area safety, as well as how they fluctuate over time.