Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)

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Deep Learning-Based Spatial Governance of Groundswell Economy

Authors
Enjue Zhao1, *
1Beijing Jiaotong University, Beijing, China
*Corresponding author. Email: zhaoenjue@outlook.com
Corresponding Author
Enjue Zhao
Available Online 26 July 2023.
DOI
10.2991/978-94-6463-200-2_146How to use a DOI?
Keywords
stall economy; spatial governance; deep learning; simulation
Abstract

As a new form of economy in the new era, the stall economy has brought new vitality to urban development. However, the rapid development of the stall economy has also brought a series of problems, among which spatial governance is one of the key factors affecting the healthy development of the stall economy. This paper proposes a research method of spatial governance of stall economy based on deep learning. Firstly, this paper analyzes the current situation and existing problems of spatial governance of stall economy from a theoretical perspective, and puts forward the application ideas of deep learning in spatial governance of stall economy. Secondly, taking the stall economy of a certain city as the research object, this paper collects the relevant data of the city and preprocesses the data. Finally, based on the deep learning model, this paper simulates the spatial governance of the stall economy and analyzes the simulation results. The experimental results show that the research method of spatial governance of stall economy based on deep learning proposed in this paper has high feasibility and practicality.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
26 July 2023
ISBN
978-94-6463-200-2
ISSN
2589-4919
DOI
10.2991/978-94-6463-200-2_146How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Enjue Zhao
PY  - 2023
DA  - 2023/07/26
TI  - Deep Learning-Based Spatial Governance of Groundswell Economy
BT  - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
PB  - Atlantis Press
SP  - 1359
EP  - 1365
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-200-2_146
DO  - 10.2991/978-94-6463-200-2_146
ID  - Zhao2023
ER  -