浙江大学学报（理学版）2025，Vol.52Issue(3)：289-299,11.DOI:10.3785/j.issn.1008-9497.2025.03.001
基于可解释性机器学习的养老产业空间布局研究
Research on the spatial layout of the elderly care industry based on explainable machine learning:A case study of Hangzhou
曾笑奇 1赵秋皓 1冯友建1
作者信息
- 1. 浙江大学 地球科学学院,浙江 杭州 310058
- 折叠
摘要
Abstract
The elderly care industry is significant for addressing the challenges of population aging.However,existing research has not sufficiently explored the factors influencing the spatial layout of elderly care facilities or how to optimally predict these layouts.This study uses Hangzhou's urban area as a case study to fill this gap.Utilizing data from the Seventh National Population Census and POI data,we compare the prediction accuracy of three machine learning models—decision tree(DT),random forest(RF),and extreme gradient boosting tree(XGBoost).The Random Forest model,which showed the highest accuracy,was further analyzed using SHAP to deeply understand the influencing factors.The results indicate that:(1)SHAP effectively interprets the results of the machine learning algorithms;(2)Most factors,such as population size and government institutions,positively impact the layout of elderly care facilities,whereas other factors,such as financial service facilities,negatively impact their layout;(3)Future construction of elderly care facilities in Hangzhou should prioritize the central districts of Shangcheng and Gongshu as well as their surrounding areas,while development in Fuyang and Lin'an districts could be moderated.These insights provide a strategic basis for optimizing the spatial distribution of elderly care facilities to better meet the needs of the aging population.关键词
养老产业/养老服务设施/空间布局/POI数据/机器学习Key words
elderly care industry/elderly care service facilities/spatial layout/POI data/machine learning分类
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曾笑奇,赵秋皓,冯友建..基于可解释性机器学习的养老产业空间布局研究[J].浙江大学学报（理学版）,2025,52(3):289-299,11.
