中国民航大学学报

• 管理科学 • 上一篇    

基于灰色马尔可夫模型的公务航空市场需求预测

孙继湖,张津君   

  1. (中国民航大学经济与管理学院,天津 300300)
  • 收稿日期:2014-04-29 修回日期:2014-05-22 出版日期:2015-06-22 发布日期:2015-07-08
  • 作者简介:孙继湖(1959—),男,河北张家口人,教授,博士,研究方向为民航运输管理.
  • 基金资助:

    中国民用航空局软科学基金项目(MHRD201048)

Prediction of business aviation market demand based on improved Grey-Markov model

SUN Ji-hu,ZHANG Jin-jun   

  1. (Economics and Management College,CAUC,Tianjin 300300,China)
  • Received:2014-04-29 Revised:2014-05-22 Online:2015-06-22 Published:2015-07-08

摘要:

当前中国公务航空在快速发展的同时也受到多方面因素的制约,针对此特点,结合灰色预测与马尔可夫链理论的优点,尝试对中国公务机的需求量进行预测。首先对原始时间序列进行改进处理,建立了GM(1,1)模型,然后用马尔可夫模型对预测值予以修正。实验结果表明,改进后的灰色马尔可夫模型预测精度有了进一步提高,能较好地应用于中国公务机市场需求量的预测,且改进方法便于操作袁有较高的实用性。

关键词: 公务航空, 市场需求, 灰色预测, 马尔可夫链

Abstract:

At present,business aviation of China has been rapidly developed,meanwhile it has been constrained by many factors such as airspace management system,industry management standards,infrastructure and so on.Considering this feature,by combining the advantages of both grey prediction and Markov theory,this research attempts to forecast the business aviation market demand in China. Firstly,the GM(1,1)model is established after improving the original time series,and then the predicted value is corrected by Markov model. Results show that the prediction accuracy of improved Grey-Markov model has been further improved. This model has not only the advantages of grey system for short-term trend accurate forecast,but also the accurately predicting advantage of Markov prediction model for volatility data. It overcomes the disadvantages of both the two predicting methods. This data processing method is straightforward and has a relatively high practicability.

Key words: business aviation, market demand, grey prediction, Markov chain

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