A Study on the Location Planning and Layout Prediction of Elderly Care Facilities in the Central Urban Area of Lanzhou City Based on a Machine Learning Model

DOI

10.2991/978-2-38476-259-0_105How to use a DOI?

Keywords

poi data; machine learning model; decision tree; senior living facilities; planning layout prediction

Abstract

Based on POI data and “seven universal” population and other data, using the decision tree model based on ID3 algorithm, according to the basic research unit of 500 m × 500 m, 4,466 research units are divided into the central urban area of Lanzhou City for machine learning simulation and training, and taking into account the characteristics of the distribution of the current urban senior care facilities, we get 961 suitable site distribution units. 961 suitable site distribution units, on the basis of which quantitative simulation predictions are made for the site layout of senior care facilities in the study area. The results show that in the future, senior care facilities can be located in the following key research units: the southern part of Hekou Town, the central part of Dachuan Town, and the northern part of Xincheng Town in Xigu District; the central part of Xiguoyuan Town, the central part of Huangyu Town, and the central part of Bali Town in Qilihe District; the central part of Shajingyi Street and the northwestern part of Anningbao Street in Anning District; and the western part of Volunping Street, the western part of Yancanglu Street, the northern part of Caochang Street, and the northern part of Jingyuan Street in Chengguan District.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yinxia Tian
AU  - Tianpeng Wang
PY  - 2024
DA  - 2024/06/21
TI  - A Study on the Location Planning and Layout Prediction of Elderly Care Facilities in the Central Urban Area of Lanzhou City Based on a Machine Learning Model
BT  - Proceedings of the 2024 3rd International Conference on Social Sciences and Humanities and Arts (SSHA 2024)
PB  - Atlantis Press
SP  - 1017
EP  - 1027
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-259-0_105
DO  - 10.2991/978-2-38476-259-0_105
ID  - Tian2024
ER  -