Research on Population Distribution Model Based on Real Estate Big Data
- DOI
- 10.2991/icmcs-18.2018.114How to use a DOI?
- Keywords
- Real estate data; Population distribution; Matrix model
- Abstract
Population distribution is one of the important factors that affects social economic vitality, infrastructure construction, public service allocation, transportation, resources and so on. Obtaining high density urban population distribution could lay a foundation for urban population management, adjustment and planning, and optimize people's living environment. Although there are many models of population distribution, few studies considered on the distribution of population in the region. Finding a good model to calculate regional population distribution could provide effective theoretical support for solving practical problems. Based on the data of urban real estate big data integration platform, the population distribution model studied in this paper. Through the results of statistical analysis of questionnaire, selected some important factors of population distribution, and carried on the in-depth analysis to these influencing factors. The weight of each factor in the population distribution model is calculated by constructing an improved matrix model. By comparing and analyzing the results of the research and the actual situation, the improved algorithm is put forward at the same time. The experiment shows that the study of population distribution model based on real estate big data is a powerful supplement to the traditional statistical model.
- 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 - Jie Dong AU - Gui Li AU - Liming Du PY - 2018/10 DA - 2018/10 TI - Research on Population Distribution Model Based on Real Estate Big Data BT - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018) PB - Atlantis Press SP - 555 EP - 559 SN - 2352-538X UR - https://doi.org/10.2991/icmcs-18.2018.114 DO - 10.2991/icmcs-18.2018.114 ID - Dong2018/10 ER -