基于灰色马尔可夫模型的公务航空市场需求预测

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

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,有较高的实用性。

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.