基于灰色-马尔可夫链改进方法的铁路货运量预测研究

Study on Railway Freight Volume Forecast by the Gray-Markov Chain Method

科学的预测对于经济现象的研究和经济决策的制定都具有十分重要的意义,因此,关于经济预测理论和方法的研究一直是一个热点。本文将灰色模型预测方法GM(1,1)和马尔可夫链预测相结合,提出灰色马尔可夫链改进预测方法,并且针对我国铁路货运量的发展趋势进行了预测,得出比灰色预测更加准确的结论。从而证明,灰色马尔可夫链改进方法的预测结果更加准确可靠,更有利于决策者的经济决策行为。

It is of very important meaning to forecast scientifically in economic phenomena research and economic policy decision, so the theory and method of economic prediction remains a hot spot in research all the time. This article combines the Gray Prediction Method GM(1,1) and Markov Prediction Method and puts forward the Gray-Markov Method. The improved Gray-Markov Method is employed to forecast the future development of the china railway freight volume. More accurate conclusions are drawn as compared with the Gray Method. It is proved that the Gray-Markov Method is more reliable and effective for policy makers.