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Updated: Sep 9, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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在干旱的城市地区使用SHAP增强的堆叠集体学习绘制洪水易感度:吉达的一个案例研究

Bilel Zerouali1, Abdulrazak H Almaliki2, Celso Augusto Guimarães Santos3

  • 1Laboratory of Architecture, Cities and Environment, Faculty of Civil Engineering and Architecture, Department of Hydraulic, Hassiba Benbouali University of Chlef, B.P. 78C, Ouled Fares, 02180, Algeria.

Journal of environmental management
|August 29, 2025
PubMed
概括

这项研究使用堆叠的机器学习和可解释的AI开发了沙特阿拉伯吉达的准确洪水易感地图. 该框架有效地确定了数据稀缺的城市环境中的高风险区域.

关键词:
对洪水易感性的绘制吉达市机器学习SHAP的可解释性沙特阿拉伯堆叠组合模型

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