通过可解释的机器学习,了解城市区块形态在创新活力的作用
Yichen Ruan1, Xiaoyi Zhang1, Jiwu Wang2
1School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.
Scientific reports
|July 2, 2025
概括
城市区块形态显著影响创新活力. 土地使用多样性,地面积比率和街道网络密度等关键因素表现出非线性和协同效应,指导城市规划以加强创新.
科学领域:
- 城市研究 城市研究
- 经济地理 经济地理
- 空间分析 空间分析
背景情况:
- 创新活动对于社会经济发展至关重要.
- 城市街区是促进创新的重要中心.
- 了解城市街区形态对创新的影响至关重要,但具有挑战性.
研究的目的:
- 分析城市区块形态特征如何影响城市创新活力.
- 研究区块形态学对创新的非线性影响和相互作用机制.
- 根据形态因素提供优化城市创新的规划策略.
主要方法:
- 使用了空间分析技术.
- 使用基于SHAP的可解释机器学习.
- 在数字创新中心杭州进行的案例研究.
主要成果:
- 土地使用多样性,地面积比率和街道网络密度被确定为最有影响力的因素.
- 区块形态证明了对创新活力的非线性影响.
- 观察到诸如街道网络密度和地板面积比率等因素之间的协同效应可以增强创新.
结论:
- 城市区块形态对创新活力具有复杂,非线性和交互性的影响.
- 该研究提供了一种有效的方法来平衡空间分析中的精度和可解释性.
- 结果为城市研究中应用复杂性科学提供实证支持,并为有针对性的规划策略提供信息.
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