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Updated: Jun 23, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Published on: July 24, 2016

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根据使用各种机器学习方法整合环境因素,绘制韩国州洪水易感性地图

Liadira Kusuma Widya1, Fatemeh Rezaie2, Woojin Lee3

  • 1Department of Science Education, Kangwon National University, 1 Gangwondaehak-gil, Chuncheon-si, Gangwon-do, 24341, Republic of Korea; Civil Engineering, Sunan Bonang University, Tuban, East Java, 62315, Indonesia.

Journal of environmental management
|June 14, 2024
PubMed
概括

机器学习模型,包括长期短期记忆 (LSTM),准确地绘制了韩国州洪水易感性的地图. 这项研究有助于为脆弱地区制定有效的洪水风险管理策略.

关键词:
提升了树的树.易受洪水影响的易感性地理信息系统 (GIS) 是一个这是LSTM的LSTM.机器学习 机器学习这是一个SVRSVR.

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