Apply Grey Markov SCGM(1,1) Model to Predict Airports Passenger Traffic in China

The amount of passengers handled at airports and its growth is basic data and also an important indicator of development of civil aviation.This article aims to use general statistical methods to reveal the changes of amount of passengers handled at airports and make accurate forecasts.The grey prediction model can be applied to the prediction of passengers handled at airports,and has a good accuracy.On this basis,we proposed the introduction of Markov chain prediction theory and the ideas to establish a grey Markov model to predict the amount of passengers handled at airports in order to make forecasts more accurate and reliable.In the example,we compared the results of grey prediction model and grey Markov prediction model and verified that the accuracy of the prediction of grey Markov model is higher than that of the grey prediction model.Thus,grey Markov model can be applied to the prediction of the amount of passengers handled at airports and can provide more accuracy than the grey model for reliable predictions.Finally,using grey Markov model,we forecasted the amount of passengers handled at airports for 2007 and 2008.