Research on logistics demand portfolio forecasting in Shandong Province based on GM(1,N) model

Huaqiong Liu; Dehao Cao; Jingyi Zhang

doi:10.1117/12.3050701

20 January 2025 Research on logistics demand portfolio forecasting in Shandong Province based on GM(1,N) model

Huaqiong Liu, Dehao Cao, Jingyi Zhang

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134220N (2025) https://doi.org/10.1117/12.3050701
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

With the rapid development of economy of globalization and e-commerce, logistics industry has become an indispensable key link in modern economic system. Logistics demand forecasting is a key link in logistics management, which plays an important role in improving logistics efficiency, reducing operating costs and optimizing resource allocation. This paper aims to discuss in detail the current situation and challenges in the field of logistics demand forecasting, select 7 influencing factors of economic indicators in Shandong Province from 2017 to 2022 as input indicators, and cargo transportation volume as the output indicators of logistics demand, and on the basis of gray correlation analysis, select several influencing factors with high correlation degree with feature series as prediction indicators, construct GM(1,7) model, use MATLAB to solve the model, and calculate the parameters. The forecast value of logistics demand in Shandong Province from 2017 to 2023 was obtained, and validity of model was tested, and the prediction of this model has high reliability and accuracy, 00with a reasonable relative error. In addition, this paper combines the present situation of logistics development in Shandong Province. Based on this, three suggestions are put forward: increasing infrastructure investment, optimizing agricultural and manufacturing logistics, and improving urban distribution network.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huaqiong Liu, Dehao Cao, and Jingyi Zhang "Research on logistics demand portfolio forecasting in Shandong Province based on GM(1,N) model", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134220N (20 January 2025); https://doi.org/10.1117/12.3050701

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KEYWORDS

Data modeling

Industry

Analytical research

Statistical analysis

Statistical modeling

Agriculture

Reliability

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