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Academic Journal of Computing & Information Science, 2020, 3(3); doi: 10.25236/AJCIS.2020.030305.

Prediction of port logistics demand based on BP neural network -- a case study of Nantong Port

Author(s)

Weize Lu*, Likun Wang

Corresponding Author:
Weize Lu
Affiliation(s)

College of Transport & Communications, Shanghai Maritime University, Shanghai, China
*Corresponding author e-mail: [email protected]

Abstract

China city's rapid economic development one after another and one belt, one road strategy is being put forward and pushed forward. The construction and planning of coastal cities' ports are becoming more and more important. The prediction of port logistics demand can provide some reference for port construction and planning. This paper analyzes the factors affecting the logistics demand of Nantong port, constructs the BP neural network model to forecast the port logistics demand of Nantong port from 2019 to 2021, and puts forward some suggestions for reference.

Keywords

Port logistics demand, BP neural network, Port, forecast

Cite This Paper

Weize Lu, Likun Wang. Prediction of port logistics demand based on BP neural network -- a case study of Nantong Port. Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 3: 34-42. https://doi.org/10.25236/AJCIS.2020.030305.

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