基于随机森林模型算法的城市创新空间演变影响要素研究
——以武汉市主城区为例

doi:10.12069/j.na.202401114

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摘要城市创新空间的发展演变存在显著差异，关注其成因及关键影响要素具有重要现实意义。文章以武汉市主城区为研究对象，运用随机森林模型这一机器学习方法，对影响研究区域内创新空间演变的因素进行分析。结果表明，随机森林模型在处理该数据集方面表现出较好的拟合效果，能够有效捕捉影响因素与创新空间演变的复杂非线性特征。同时，该模型还揭示了影响创新空间演变的重要因素为人口密度、距商业中心距离、地铁站密度和路网密度。基于以上分析，为城市创新空间未来的发展提出建议。

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	陈从心　张萍　韩叙

关键词 ：创新空间演变, 机器学习, 数学模型, 随机森林, 武汉市

Abstract：The evolution of urban innovation space development varies greatly, and it is of great practical significance to pay attention to its causes and the key influencing factors of its evolution. Taking Wuhan main city as an example, the machine learning algorithm, and Random Forest Modeling Algorithm is used to analyze the influencing factors on the evolution of Wuhan’s innovation space. The results show that the Random Forest Modeling algorithm fits the dataset well, can effectively capture the complex nonlinear characteristics of the influencing factors and the evolution of innovation space, and reveals that the important factors affecting the evolution of the innovation space are population density, distance from commercial centers, subway station density and road network density. Finally, we make suggestions for the future development of urban innovation space based on this evidence.

Key words： innovation space evolution machine learning mathematical model random forest Wuhan

引用本文:

陈从心　张萍　韩叙. 基于随机森林模型算法的城市创新空间演变影响要素研究 ——以武汉市主城区为例[J]. 新建筑, 2024, 42(1): 114-117.
CHEN Congxin　ZHANG Ping　HAN Xu. Research on the Influential Elements of Urban Innovation Space Evolution Based on Random Forest Model Algorithm: Taking Wuhan Main City as an Example. New Architecture, 2024, 42(1): 114-117.

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https://116.62.217.67/XJZ/CN/10.12069/j.na.202401114 或 https://116.62.217.67/XJZ/CN/Y2024/V42/I1/114