| Issue |
SHS Web Conf.
Volume 181, 2024
2023 International Conference on Digital Economy and Business Administration (ICDEBA 2023)
|
|
|---|---|---|
| Article Number | 03023 | |
| Number of page(s) | 5 | |
| Section | Supply Chain Management and Logistics | |
| DOI | https://doi.org/10.1051/shsconf/202418103023 | |
| Published online | 17 January 2024 | |
Research on the application of cellular automata and improved BP neural network in road design of logistics park
Zhejiang Gongshang University Hangzhou College of Commerce, Hangzhou, 311500, China
* Corresponding author: 1180232@zjhzcc.edu.cn
With large-scale construction of the Logistics Parks, it has become an urgent problem to quantitatively analyze, evaluate and optimize the logistics park designing, which needs to be solved scientifically. At present, more of the domestic logistics park planning of a part of the qualitative analysis, the lack of quantitative and overall study, resulting in internal structure disjointed. Based on cellular automata theory, this paper presents a hybrid traffic flow model which is more suitable for the traffic characteristics of the logistics park, and analyzes the complexity of the collection and evacuation system in the logistics park, combined with BP neural network and its improved algorithm, the method of road design in Logistics Park is studied and the feasibility and validity of the model and algorithm are verified by an example. The train of thought is expected to provide for the planning and construction of the internal road in the logistics park.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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