【摘要】 灰色预测适合于原始数据序列按指数规律变化的问题,而马尔柯夫适用于预测随机波动大的动态过程.有机地结合两者构成灰色马尔柯夫预测方法,可发挥两者的优势,从而提高预测精度.该方法首先用GM(1,1)模型进行预测,而后对相对误差序列进行马尔柯夫预测,最后用该预测值修正GM(1,1)的预测结果,因而具有较高的预测精度.使用灰色马尔柯夫预测方法对苏州某交叉口实时交通量进行预测,预测结果优于单一灰色GM(1,1)预测.实验表明,灰色马尔柯夫预测方法用于交通量预测是有效可行的.更多还原

【Abstract】 Grey model is fit to forecast the original data series varied by exponent rules,and Markov model is suitable for forecasting dynamic process with large stochastic wave.Combining grey model with Markov model can obtain Grey Markov forecasting model,which employs the advantages of both methods and improves the forecasting precision further.This hybrid model firstly used GM(1,1) to forecast the raw data,then applied Markov model to forecast relative error series,at last used the forecasting relative error data to amend GM(1,1) result.So this method has a high predicting precision.Grey Markov forecasting model was employed to forecast real time traffic volume of an intersection in Suzhou city.The example showed that forecasting results were in good agreement with the measured data,and the model had overmatched simplex GM(1,1).The traffic volume forecasting based on Grey Markov model is of validity and feasibility.更多还原