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Updated: Jul 13, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

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推进阿拉巴马州沿海住宅物业的洪水损害建模:一种多变量机器学习方法

Mujungu Lawrence Museru1, Rouzbeh Nazari2, Abolfazl N Giglou1

  • 1Sustainable Smart Cities Research Center, University of Alabama at Birmingham (UAB), Birmingham, AL, USA; Department of Civil, Construction, and Environmental Engineering, University of Alabama-Birmingham, Birmingham, AL 35294-4440, USA.

The Science of the total environment
|October 18, 2023
PubMed
概括

准确的洪水风险预测至关重要. 这项研究使用机器学习和过量采样技术增强了洪水损害评估模型,提高了受损物业和相对洪水损害的预测准确度.

关键词:
整合机器学习 机器学习洪水风险评估 洪水风险评估多变量洪水损害模型在SHAP中,SHAP值是指SHAP值.在SMOTE中使用.

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Watershed Planning within a Quantitative Scenario Analysis Framework

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