Data Mining Research on Beijing Population Growth

DOI

10.2991/emcs-17.2017.14How to use a DOI?

Keywords

Beijing population growth; Correlation analysis of SPSS; Logistic model; Granger causality test

Abstract

In this paper, a significant increase in population in Beijing the status quo, analysis of Beijing Population significant increase in the status quo, to identify relevant factors by reading literature, summed up the result of the rapid population growth in Beijing 30 factors, and to all the factors grouped into six Primary categories: population-related classes, economic level class, consumption level class, employment category, Education, income class. The use of official statistics, SPSS software through this six categories of basic data correlation detection and analysis of the factors that influence the focus, and then focus by Eviews software calibration factors affecting Granger causality, ultimately derived six kinds caused a significant increase in population in Beijing strong correlation factor people use in recent years, Beijing building data using logistic models to predict population growth in Beijing.

Copyright

© 2017, 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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TY  - CONF
AU  - Xinfang Song
PY  - 2017/03
DA  - 2017/03
TI  - Data Mining Research on Beijing Population Growth
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 69
EP  - 75
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.14
DO  - 10.2991/emcs-17.2017.14
ID  - Song2017/03
ER  -