Innovative practices in facility location based on machine learning:A case study of neighborhood centers in Shenyang City
LI Yuan
YU Sitao
WANG Shuai
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.
Keywords：neighborhood centercore development sectormachine learningmulti-source datadetailed planning and implementation
Publication Date：2025-10-25
Pages：5( 82-86 )