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首页> 外文期刊>Journal of Mathematics >Forecast of Freight Volume in Xi’an Based on Gray GM (1, 1) Model and Markov Forecasting Model
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Forecast of Freight Volume in Xi’an Based on Gray GM (1, 1) Model and Markov Forecasting Model

机译：基于灰色通用（1,1）模型和马尔可夫预测模型的西安货运量预测

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摘要

Due to the continuous improvement of productivity, the transportation demand of freight volume is also increasing. It is difficult to organize freight transportation efficiently when the freight volume is quite large. Therefore, predicting the total amount of goods transported is essential in order to ensure efficient and orderly transportation. Aiming at optimizing the forecast of freight volume, this paper predicts the freight volume in Xi’an based on the Gray GM (1, 1) model and Markov forecasting model. Firstly, the Gray GM (1, 1) model is established based on related freight volume data of Xi’an from 2000 to 2008. Then, the corresponding time sequence and expression of restore value of Xi’an freight volume can be attained by determining parameters, so as to obtain the gray forecast values of Xi’an’s freight volume from 2009 to 2013. In combination with the Markov chain process, the random sequence state is divided into three categories. By determining the state transition probability matrix, the probability value of the sequence in each state and the predicted median value corresponding to each state can be obtained. Finally, the revised predicted values of the freight volume based on the Gray–Markov forecasting model in Xi’an from 2009 to 2013 are calculated. It is proved in theory and practice that the Gray–Markov forecasting model has high accuracy and can provide relevant policy bases for the traffic management department of Xi’an.
机译：由于生产率的不断提高，货运量的运输需求也在增加。当货运量相当大时，很难有效地组织货运运输。因此，预测运输的货物总额至关重要，以确保有效且有序地运输。旨在优化货运量预测，本文以灰色通用（1,1）模型和马尔可夫预测模型预测西安货运量。首先，基于2000年至2008年的西安的相关货运量数据建立了灰色GM（1,1）模型。然后，通过确定可以获得相应的时间序列和恢复价值的恢复值的表达参数，从2009年到2013年获得西安货运量的灰色预测值。与马尔可夫链过程结合，随机序列状态分为三类。通过确定状态转换概率矩阵，可以获得每个状态中的序列的概率值和对应于每个状态的预测中值值。最后，计算了2009年至2013年基于西安灰马尔可夫预测模型的货运量的修订预测值。理论和实践证明，灰色马尔可夫预测模型具有高精度，可为西安交通管理部门提供相关政策基础。

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