Aviation Accident Prediction Based on Auto-Regressive Integrating Moving Average Method
Xu Gan, Jing Shun Duanmu, Jian Guo Gao · Advanced materials research · 2013
In order to reinforce the efficiency and initiative of accident prevention for reducing accident loss, the surest way is to strengthen the prediction. In view of difficulties in aviation accident prediction, a prediction method based on Auto-Regressive Integrating Moving Average (ARIMA) is proposed. In this method, a trial model is first identified for an accident time series, and then the diagnosis is executed with the necessary adjustments. The calculation process including identification, estimation and diagnosis is repeated until obtain a satisfactory model. The example shows that, ARIMA has a good prediction for aviation accident and provides an important technique support for decision-making of aviation safety.