Identification Of Terminal Area Traffic Situation

With the fast development of civil aviation industry, airport flow is also rising. The capacity of airport is even more difficult to meet the growing traffic demand, making the phenomenon of flight delays often occurs in our country, and terminal area traffic conditions is one of the issues that people are most concerned about. Congestion not only deploy follow-up flights more difficult, but also cause a wide range of delays. Accurate grasp of the terminal area traffic situation is not only a premise of research, but also development of efficient decision support system. Therefore, how distinguish traffic situation of terminal area become an research focus.The current situation of congestion and situation is analyzed, and the terminal area traffic situation perception model is established. The reasons for congestion and congestion caused by the impact are analyzed, evaluation parameters of terminal area traffic situation are analyzed in-depth. The concept of unbalanced degree and calculation methods is posed, and analysis it based on the Lorenz curve. The average delay time is normalized based on unbalanced degree, and proposed the complexity which described the aircraft spatial relationships in terminal area.Terminal area traffic situation is identified based on fuzzy reasoning. Put each factor as an input parameter, state terminal area traffic situation index or terminal area traffic situation as an output parameter, using fuzzy C-means clustering algorithm and fuzzy C-means clustering- Recognition of rough set algorithm analyzes the traffic situation of the terminal area.Using historical data to a terminal area, complexity and the uneven spatial distribution of the aircraft were calculated and analyzed; establishing two fuzzy inference terminal area traffic situation recognition systems in MATLAB simulation and numerical examples of the two the effect of species identification system were analyzed and compared.