Research Article
Study on Civil Aviation Unsafe Incident Prediction Based on Markov Optimization
@INPROCEEDINGS{10.1007/978-3-030-19086-6_58, author={Fei Lu and Wenya Li and Zhaoning Zhang and Kexuan Liu}, title={Study on Civil Aviation Unsafe Incident Prediction Based on Markov Optimization}, proceedings={Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings}, proceedings_a={ADHIP}, year={2019}, month={5}, keywords={Unsafe event Gray model Combination forecast Markov optimization}, doi={10.1007/978-3-030-19086-6_58} }- Fei Lu
Wenya Li
Zhaoning Zhang
Kexuan Liu
Year: 2019
Study on Civil Aviation Unsafe Incident Prediction Based on Markov Optimization
ADHIP
Springer
DOI: 10.1007/978-3-030-19086-6_58
Abstract
The civil aviation safety management system requires accurate prediction of the future safety status, but there are often many uncertain factors in the occurrence of air traffic insecurity events. In order to study its development trend and strengthen the accurate analysis and prediction of unsafe events, a combined forecasting model based on Markov correction process is proposed. Firstly, apply the grey system theory to construct a GM (1, 1) model. Then, based on the grey prediction model and the exponential smoothing method, combination forecasting model is established. And according to the standard deviation of the prediction result, the weight is determined to correct the data. Finally, combined with the Markov method, the probability transfer matrix is determined and the results are optimized. Based on the statistics of civil aviation insecure events in the past ten years, the prediction accuracy of the optimized model is significantly higher than that of the single gray prediction model or the exponential smoothing prediction model, which verifies the effectiveness of the method.
