香港国际机场航空交通量的无偏灰色马尔科夫预测

Application of Dynamic Unbiased Grey Markov Model in Prediction of Air Traffic Flow at Hong Kong International Airport

针对香港国际机场航空交通量的灰色性和随机波动性,本文采用无偏灰色GM（1,1）代替传统灰色GM（1,1）模型,分析了2001-2012年香港机场航空交通量的数据,预测出2013年香港机场的航空交通量,然后用加权马尔科夫模型对预测结果进行优化.利用Matlab计算得后验差检验C值小于0.35,P值为1,拟合精度等级为好,表明动态无偏灰色马尔科夫能消除传统灰色GM（1,1）模型的固有误差,提高预测精度.加权马尔科夫模型对灰色预测结果优化得2013年香港航空交通量在352 241～370 780架次之间.

Considering the grey and random fluctuation of air traffic flow at Hong Kong interna- tional airport, dynamic unbiased grey Markov model is proposed to fit the development tendency of air traffic flow at Hong Kong international airport by analyzing the air traffic flow from 2001 to 2012. And the air traffic flow in 2013 is forcasted. Then Optimize the prediction result using weighted Markov model. Posterior error calculated C value of less than 0.35, P value of 1. Fitting accuracy is good. The results show that DUGM-Markov eliminates the inherent bias of the traditional GM（1,1） model and the prediction accuracy is much higher. Using this model, the air traffic flow at Hong Kong international airport in 2013 is predicted to be between 352241 and 370780 flights.