Proceedings of the 5th International Conference on Financial Innovation and Economic Development (ICFIED 2020)

The Economic Research of All Provinces in China Based on Cluster Analysis

Authors
JI Shi
Corresponding Author
JI Shi
Available Online 11 March 2020.
DOI
10.2991/aebmr.k.200306.019How to use a DOI?
Keywords
cluster analysis, MATLAB, economic type
Abstract

The economic type of a province is affected by many factors, such as geographical location, GDP, population quality and so on. In this paper, MATLAB software is used to analyze the five factors of economic types, including the Gross Regional Product (billion yuan), the gross production of agriculture, forestry, animal husbandry and fishery (billion yuan), the gross output of construction industry (billion yuan), the total population (10000 people), and the total import and export volume (1000 US dollars) of the place where the business unit is located in 2018, so as to explore the development of national economy. The data comes from National Bureau of Statistics.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 5th International Conference on Financial Innovation and Economic Development (ICFIED 2020)
Series
Advances in Economics, Business and Management Research
Publication Date
11 March 2020
ISBN
10.2991/aebmr.k.200306.019
ISSN
2352-5428
DOI
10.2991/aebmr.k.200306.019How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - JI Shi
PY  - 2020
DA  - 2020/03/11
TI  - The Economic Research of All Provinces in China Based on Cluster Analysis
BT  - Proceedings of the 5th International Conference on Financial Innovation and Economic Development (ICFIED 2020)
PB  - Atlantis Press
SP  - 109
EP  - 112
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200306.019
DO  - 10.2991/aebmr.k.200306.019
ID  - Shi2020
ER  -