Research Of Grey Prediction On Early Warning Of Risk In Air Traffic Management

With the continued growth of our economy, the civil aviation transportation has beening developed rapidly, which brings pressure and more strict requirements to the air traffic management(ATM) system of our country. From the point of operation of ATM system, only use scientific and reasonable methods to predict the risk of ATM system and warn, can it improve the efficiency of the air traffic control and ensure the safety of the aircraft.The research of risk of ATM operation is focused on the analysis of risk factors and the prediction and early warning of risk. The change rules of risk factors should be explored from the source.This study is based on the problem about early warning and decision-making of risk of ATM operation. Risk factors and statistics are extracted from related references. Then the risk factors are analyzed and classified by the method of SHEL model. At the same time, The warning assessment index system of runway risk with second structure is established according to the criterion of safety evaluation.Grey theory is applied in this stduy and research based on a case study of runway risk is carried on. It conducts correlation analysis of risk factors and determines influence degree of risk factors to risk events. It combines grey prediction and neural network model. In the study, Grey prediction method is used to predict the single risk factor and improve the neural network model by multiple factors input. Then a stable network model is developed through neural network training for many times and makes scientific prediction to risk. Meanwhile system dynamics model is introduced to research ATM system and analyze feedback relation of cause and effect between various risk factors. The study also establishes risk flow diagram of operation risk of system and simulates through the adjustment of structure and parameters. On the basis of research above, corresponding alarm mode is setted and used to make reasonable plans of early warning and response decision-making about risk. Finally the goal is to realize effective forecast and early warning of the risk of ATM operation and provide effective theory methods and decisions basis for the management of risk of ATM.