摘要
以黄河三角洲的221个村落为研究样本,提取河、塘、田、路4个主要影响因子,构建环境因子、平面形态和空间结构指标数据库,运用机器学习方法,定量分析环境因子对村落空间形态的影响,逐步揭示环境因子对村落空间形态的作用过程。数字化的统计分析与模型预测,可以更准确地识别这种非线性变化下的重要因素,使村落空间形态研究以及未来乡村建设更具科学性。
This paper takes 221 villages in the Yellow River Delta as research samples,extracts four main influencing factors,namely,river,pond,field and road,builds a database of environmental factors,plane shape and spatial structure indicators,uses machine learning methods to quantitatively analyze the impact of environmental factors on the spatial form of villages,and gradually reveals the process of the impact of environmental factors on the spatial form of villages.Digital statistical analysis and model prediction can more accurately identify the important factors under such nonlinear changes,making the research on village spatial morphology and future rural construction more scientific.
作者
孔亚暐
赵子玉
关增达
赵以恒
郭立强
KONG Yawei;ZHAO Ziyu;GUAN Zengda;ZHAO Yiheng;GUO Liqiang
出处
《建筑学报》
北大核心
2023年第S02期70-75,共6页
Architectural Journal
基金
国家重点研发计划课题(2019YFD1100801)
关键词
流域环境
黄河三角洲
乡村聚落
空间形态
机器学习
成因
basin environment
Yellow River Delta
rural settlement
spatial morphology
machine learning
cause
