Author
Listed:
- Anping Zha
- Jianjun Tu
- Naeem Jan
Abstract
After entering the new century, along with the further deepening of global economic and trade cooperation, the industrial division of labor has been newly developed globally, which brings the cooperation among countries in the international logistics chain more and more closely. As the core node linking domestic and foreign water transportation, ports play a very key role in the international logistics chain and have an extremely central position in the national logistics planning. The coordinated development of port economy is an important part of the economic development planning of port cities, and it is also the premise and basis for the comprehensive planning of port logistics infrastructure construction scale, logistics space layout, and port city logistics development direction and function positioning. Therefore, according to the availability of realistic data, this paper establishes a deep neural network prediction model for the collaborative development of ports and uses various port logistics indicators to predict the economic development trend, so as to realize a nonlinear mapping relationship between the level of port economic development and the side of port logistics demand. Meanwhile, the research of this paper will provide theoretical basis and corresponding practical tools for the coordinated development between regional economy and port logistics industry.
Suggested Citation
Anping Zha & Jianjun Tu & Naeem Jan, 2022.
"Research on the Prediction of Port Economic Synergy Development Trend Based on Deep Neural Networks,"
Journal of Mathematics, Hindawi, vol. 2022, pages 1-9, April.
Handle:
RePEc:hin:jjmath:8052957
DOI: 10.1155/2022/8052957
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jjmath:8052957. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.