在灰色预测的基础上，引入马尔可夫链预测理论，建立了灰色马尔可夫预测模型。它是将灰色预测模型与马尔可夫预测方法优化组合，用灰色预测模型预测随机时间序列数据的总体发展趋势，而用马尔可夫链模型预测各数据在总体趋势下的随机波动性变化，得到随机时间序列趋势预测模型的解。通过公路运输实际数据进行了验证，结果表明：灰色马尔可夫预测模型既能预测随机数据序列的总体趋势，又适应波动性较大的随机序列变化，灰色马尔可夫预测模型预测精度高于GM(1，1) 模型的预测精度。

Based on the gray method of forecast, the Markov chains forecast method is presented and a grayMarkov model for forecast is proposed in this paper. The solution of the statistical model is got by the merits combination of both gray forecast and the Markov forecast, a gray system model is used to forecast the general trend of the data series’ changing status, and a time series Markov chain model is used to forecast the fluctuation of data change along the general trend. The example of highway transport enterprise shows that the model can well and truly forecast the evolvement and the changing trend of the data series status. The precision of the grayMarkov model for forecast is better than that of the gray model.