智能城市2025，Vol.11Issue(10)：82-86,5.DOI:10.19301/j.cnki.zncs.2025.10.019
基于机器学习的设施选址技术创新实践
Innovative practices in facility location based on machine learning:A case study of neighborhood centers in Shenyang City
李源 1于思涛 1王帅1
作者信息
- 1. 沈阳市规划设计研究院有限公司,辽宁 沈阳 110000
- 折叠
摘要
Abstract
The article explores how to promote the construction of neighborhood centers and living circles by focusing on core development areas,thereby effectively implementing detailed urban planning and conveying planning intentions.Taking the nine urban districts of Shenyang as an example,at a 500-meter grid scale,it innovatively employs a machine learning-based random forest model,combined with the existing distribution of neighborhood centers,and uses point-of-interest(POI)big data to scientifically simulate and predict potential site locations for neighborhood centers in Shenyang.At the same time,considering the distribution of Shenyang's core development areas,95 priority layout sites are ultimately selected.Different construction and guidance recommendations are proposed for neighborhood center points inside and outside the core development areas,aiming to promote the sustainable development of neighborhood centers in Shenyang and provide strong support for the city's future planning.关键词
邻里中心/核心发展板块/机器学习/多源数据/详细规划实施Key words
neighborhood center/core development sector/machine learning/multi-source data/detailed planning and implementation分类
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李源,于思涛,王帅..基于机器学习的设施选址技术创新实践[J].智能城市,2025,11(10):82-86,5.
