In-Depth Analysis of Railway and Company Evolution of Yangtze River Delta with Deep Learning

المؤلفون المشاركون

Gui, Renzhou
Chen, Tongjie
Nie, Han

المصدر

Complexity

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-25، 25ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-01-21

دولة النشر

مصر

عدد الصفحات

25

التخصصات الرئيسية

الفلسفة

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1142307