Sustainable Development of Urban Agglomeration Industrial Layout Based on Big Data and Deep Learning

被引：0

作者：

Gui, Renzhou ^{[1
]}

Zheng, Huilin ^{[1
]}

Ji, Xiaohong ^{[1
]}

Chen, Tongjie ^{[1
]}

Pang, Chuan ^{[2
]}

Liu, Chengkun ^{[2
]}

机构：

[1] Tongji Univ, Dept Elect & Commun Engn, Shanghai, Peoples R China

[2] Macau Univ Sci & Technol, Sch Business, Macau, Peoples R China

来源：

2021 PHOTONICS & ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS 2021) | 2021年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/PIERS53385.2021.9695070

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Sustainable development of smart cities is a new trend of urban development in the world. The regional development of urban agglomerations is not balanced, which makes it difficult to achieve sustainable development of smart cities. The railway network plays an important role in building bridges between cities. In this paper, the emerging big data and deep learning methods are used to conduct in-depth analysis on the distribution data of enterprises in the Yangtze River Delta region during the past 40 years. What's more, the connection and influence of railway development on urban agglomerations and among cities was explored. Such technologies as data capture, analysis, modeling and prediction can also be used for the sustainable development of other smart cities.

引用

页码：2492 / 2498

页数：7

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