Flight Incidents Prediction Based on Model of X-12 and ARIMA

Abstract

In order to provide scientific advice for civil aviation safety management, this paper analyzes and forecasts the fluctuation rules of Chinese civil aviation incidents. For the said purpose, a research based on the time series of the monthly incidents per 10000 flight hours from 2006–2016 year was done by model of X–12 seasonal adjustment multiplication. And then the time series was decomposed into seasonal periodic components, trend components, and random components. On this basis, the Autoregressive Integrated Moving Average (ARIMA) model, the trend regression model and the mean value method were used to predict the sequence of each sequence respectively. The X–12 multiplication model was used to restore the fitting value and the prediction value of the frequency of the accident, and the actual data were used to verify the value. The results show that: the monthly incidents per 10000 flight hours from 2006–2016 year have obvious trends and seasonality. September and April each year are the most affected by the seasons, and December and January are the least affected by the seasons; in the long run, the 2006–2008 year trend is declining, the 2009–2016 year trend is fluctuating, and the other stages tend to be stable. The prediction results show that the accuracy is more reliable. In 2017, the highest monthly incidents per 10000 flight hours is in October and the second in June.