Land Price Dynamics: An Interpretable Machine Learning Approach

dc.contributor.author	Lee, Changro
dc.date.accessioned	2026-08-20T21:01:10Z
dc.date.available	2026-08-20T21:01:10Z
dc.date.copyright	2025/11/25
dc.date.issued	2026
dc.identifier.other	JUPDDM.UPENG-5829.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4313826
dc.description.abstract	Abstract Land prices are a crucial aspect of urban planning and property valuation, and as cities grow, their dynamics become increasingly complex. Machine learning has been actively employed since the mid-2010s to capture these intricate relationships, ...
dc.publisher	American Society of Civil Engineers
dc.title	Land Price Dynamics: An Interpretable Machine Learning Approach
dc.type	Journal Article
dc.journal.volume	152
dc.journal.issue	1
dc.journal.title	Journal of Urban Planning and Development
dc.identifier.doi	10.1061/JUPDDM.UPENG-5829
dc.journal.fristpage	04025084-1
dc.journal.lastpage	04025084-9
dc.page	9
dc.tree	Journal of Urban Planning and Development:;2026:;Volume ( 152 ):;issue: 001
dc.contenttype	Fulltext