TEM Research Based on Bayesian Network and Neural Network

Abstract

This paper established the structural database using the method of Threat and Error Management (TEM), and obtained the characteristics of three types of data which are classified by threat, error and unexpected situation. Based on TEM frame, Neural Network is applied to add data, and Bayesian Network is applied to study the correlation among threat, error and unexpected situation. Here comes the conclusion: 1) Through applying Bayesian Evaluation to 625 selected samples, we found that specific unexpected situations have high correlation with some specific threat and error, Bayesian Evaluation reveals that when some unexpected situation happen, the high correlated threat and error to the unexpected situation. For instance, the threat and error that have highest correlation to in air unexpected situation are: Procedure Internal threat and communication error among Air Traffic Control and aircrew. 2) The high occurrence of some threat and error don’t necessarily have high correlation with some high unexpected situation; high probability of some threat and error don’t necessarily lead to unexpected situation. Research achievements provide data analysis skill to Air Traffic Control on safety management control, who could make corresponding prevention measure.