基于分数阶灰色马尔可夫模型的港口货物吞吐量预测研究

Research on Port Cargo Throughput Prediction Based on Fractional Order Grey Markov Model

预测港口货物吞吐量有助于港口管理者更好地了解港口的运作效率和运输流程,精确地规划港口的建设和发展,确保港口能够满足未来的货运需求。文章基于2011—2022年福州港货物吞吐量历史数据,利用分数阶灰色马尔可夫模型(FGM (1,1)模型)对福州港未来三年货物吞吐量进行预测。结果表明,与传统的GM (1,1)模型和FGM (1,1)模型相比,新的模型预测精度更高,预测值与实际值拟合度更高,预测结果可以为港口的总体布局、建设规模以及集疏运等配套设施的建设和经济的发展提供有力的支持。

Predicting port cargo throughput helps port managers better understand the operational efficiency and transportation processes of the port,accurately plan the construction and development of the port,and ensure that the port can meet future freight needs.This article is based on the historical data of cargo throughput at Fuzhou Port from 2011 to 2022,and uses a fractional order grey Markov model(FGM(1,1)model)to predict the cargo throughput of Fuzhou Port in the next three years.The results show that compared with the traditional GM(1,1)model and FGM(1,1)model,the new model has higher prediction accuracy and a higher degree of fit between the predicted and actual values.The prediction results can provide strong support for the overall layout,construction scale,construction of supporting facilities such as collection and distribution,and economic development of the port.