基于灰色加权马尔可夫链的大连铁路客运量预测

Forecasting of Railway Passenger Based on Gray-Weighted Markov Model

以2003-2013年大连铁路客运量数据为基础,采用灰色GM（1,1）模型预测方法和马尔可夫链相结合的方法对大连铁路客运量数据进行预测,给出了灰色加权马尔科夫链预测模型.不仅构造了状态转移概率矩阵,而且也获得了有效的滞时阶数.结果表明,在预测值与真实值的平均绝对误差方面,与灰色GM（1,1）模型相比,灰色加权马尔可夫链模型减小了一半,其预测效果十分理想.在此基础上,对2014-2020年大连铁路客运量数据进行了预测.

Based on the number of railway passengers from 2003 to 2013, the GM （ 1,1 ） and Markov chain models are used to predict the number of Dalian railway passengers, and Gray-Weighted Markov chain Model is proposed to construct the state transition probability matrix and achieve effective lag order number. The results show that compared with GM （ 1,1 ）, the mean absolute error of the real value and forecasted data are reduced by half through the gray-weighted Markov chain mJPodel, and the prediction effect is very ideal. On this basis, the number of Dalian railway passenger from 2014 to 2020 is forecasted.