基于“回归+马尔可夫”组合模型的民用航空事故症候数预测  

Prediction of the number of accident symptoms in civil aviation based on“regression+Markov”combined model

作　　者：王华友 张诚诚[2] 薛海红 刘轶斐[2] WANG Huayou;ZHANG Chengcheng;XUE Haihong;LIU Yifei(School of Mechatronics,Northwestern Polytechnical University,Xi’an 710072,China;The First Aircraft Institute,Aviation Industry Corporation of China,Xi’an 710089,China)

机构地区：[1]西北工业大学机电学院,陕西西安710072 [2]中国航空工业集团公司第一飞机设计研究院,陕西西安710089

出　　处：《系统工程与电子技术》2023年第7期2114-2120,共7页Systems Engineering and Electronics

摘　　要：民航事故症候数预测对于民航安全具有重要的意义。准确的预测民航事故症候数的发展趋势可以指导采取合适的事故预防措施,从而尽可能地减少民航事故数。本文在回归模型的基础上,发展了“回归+马尔可夫”组合模型来进行民用航空事故症候数的预测。其中回归模型用于发展趋势项的预测,马尔可夫模型用于随机干扰项的预测。通过中国民航局以及国家统计局发布的2006~2020年的历史统计数据,计算了回归模型、GM(1,1)灰色模型和“回归+马尔可夫”组合模型的拟合及测试误差。结果表明,“回归+马尔可夫”组合模型的拟合精度以及测试精度相比单一模型均得到了有效提高。Prediction of the number of civil aviation accident symptoms is of great significance to civil aviation safety.Accurate prediction of the development trend of the number of civil aviation accident symptoms can guide the adoption of appropriate accident prevention measures,so as to reduce the number of civil aviation accidents as much as possible.Based on the regression model,this paper develops a combined model of“regression+Markov”to predict the number of accident symptoms in civil aviation.The regression model is used to predict the trend term and the Markov model is used to predict the random disturbance term.Based on the historical statistical data of Civil Aviation Administration of China(CAAC)and National Bureau of Statistics from 2006 to 2020,the fitting and test errors of regression model,GM(1,1)and“regression+Markov”combined model are calculated.The results show that the fitting goodness and test accuracy of“regression+Markov”combined model are improved effectively compared with the single model.

关 键 词：民航 事故症候预测 回归+马尔可夫 灰色模型 

分 类 号：V37[航空宇航科学与技术—航空宇航推进理论与工程]