基于改进型灰色马尔可夫模型的公路货运价格预测

Prediction of Highway Freight Price Based on Improved Grey-Markov Model

公路货运价格是反映运输市场状况的重要指标,准确的运价数据预测有助于科学的把握市场的变化规律,并为政府相关政策的制定和运输企业市场决策提供支持。本文选取灰色马尔可夫模型对公路货运价格进行预测,由于传统的灰色马尔可夫模型中往往采用转移状态区间的中值来修正预测,预测结果不够精确。为此,本文构建改进灰色马尔可夫模型,根据转移状态为离散型随机变量这一特征,利用状态区间中值的期望对预测结果进行修正,提高了预测精度。最后以2016年7月至9月期间成都至南昌公路货运价格指数作为预测对象进行了实证分析,验证了改进模型的有效性。

The price of highway freight transportation is an important index that reflects the status of the logistics market. Accurate price forecast can help understand the market trend, and support relevant policy and decision making for the government and logistics companies. The paper use improved Gray-Markov model to forecast the highway freight price. Compared to the conventional Gray-Markov model that uses the median value of the transition state interval to adjust the prediction result, the improved Gray-Markov model treat and the transition state as a discrete random variable, therefore it leads to more accurate prediction result. The proposed model is validated based on real-world price data of highway freight transportation from Chengdu to Nanchang from July 2016 to September 2016.