Proceedings of the 2018 4th International Conference on Humanities and Social Science Research (ICHSSR 2018)

The Current Situation and Prediction of Urbanization in China Based on ARIMA Model

Authors
Yue Zhou
Corresponding Author
Yue Zhou
Available Online May 2018.
DOI
10.2991/ichssr-18.2018.14How to use a DOI?
Keywords
Urbanization, Prediction, ARIMA Model.
Abstract

This document introduces the current situation of urbanization in our country, and analyzes the development trend and the existing problems in the process of urbanization in our country. Then using the basic theory of ARIMA model in sequence theory and combining with the data of urbanization level in our country, this article use E-views and SPSS software to model and predict the urbanization rate data of China from 1982 to 2016. The results show that using ARIMA (0,2,1) model to predict the level of urbanization in China is more accurate in short-term data, which indicates that the urbanization level in our country develops more rapidly and shows a gradual upward trend.

Copyright
© 2018, 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 2018 4th International Conference on Humanities and Social Science Research (ICHSSR 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
May 2018
ISBN
10.2991/ichssr-18.2018.14
ISSN
2352-5398
DOI
10.2991/ichssr-18.2018.14How to use a DOI?
Copyright
© 2018, 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  - Yue Zhou
PY  - 2018/05
DA  - 2018/05
TI  - The Current Situation and Prediction of Urbanization in China Based on ARIMA Model
BT  - Proceedings of the 2018 4th International Conference on Humanities and Social Science Research (ICHSSR 2018)
PB  - Atlantis Press
SP  - 69
EP  - 76
SN  - 2352-5398
UR  - https://doi.org/10.2991/ichssr-18.2018.14
DO  - 10.2991/ichssr-18.2018.14
ID  - Zhou2018/05
ER  -