In-Depth Analysis of Railway and Company Evolution of Yangtze River Delta with Deep Learning
Joint Authors
Gui, Renzhou
Chen, Tongjie
Nie, Han
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-25, 25 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-21
Country of Publication
Egypt
No. of Pages
25
Main Subjects
Abstract EN
The coordinated development of smart cities has become the goal of world urban development, and the railway network plays an important role in this progress.
This paper proposes a solution that integrates data acquisition, storage, GIS visualization, deep learning, and statistical correlation analysis to deeply analyze the distribution data of companies collected in the past 40 years in the Yangtze River Delta.
Through deep learning, we predict the spatial distribution of the company after the opening of the train stations.
Through statistical and correlation analysis of the company’s registered capital and quantity, the urban development relationship under the influence of the opening of the railway is explored.
Going forward, the use and application of such analysis can be tested for use and application in the context of other smart cities for specific aspects or scale.
American Psychological Association (APA)
Gui, Renzhou& Chen, Tongjie& Nie, Han. 2020. In-Depth Analysis of Railway and Company Evolution of Yangtze River Delta with Deep Learning. Complexity،Vol. 2020, no. 2020, pp.1-25.
https://search.emarefa.net/detail/BIM-1142307
Modern Language Association (MLA)
Gui, Renzhou…[et al.]. In-Depth Analysis of Railway and Company Evolution of Yangtze River Delta with Deep Learning. Complexity No. 2020 (2020), pp.1-25.
https://search.emarefa.net/detail/BIM-1142307
American Medical Association (AMA)
Gui, Renzhou& Chen, Tongjie& Nie, Han. In-Depth Analysis of Railway and Company Evolution of Yangtze River Delta with Deep Learning. Complexity. 2020. Vol. 2020, no. 2020, pp.1-25.
https://search.emarefa.net/detail/BIM-1142307
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142307