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Updated: Feb 2, 2026

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空间时间预测和地下水储存异常的归因使用增强的混合深度学习建模与不确定性量化

Jina Yin1, Xinyao Hu2, Tongchao Nan1

  • 1State Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing, China.

Journal of environmental management
|January 31, 2026
PubMed
概括

先进的混合深度学习模型通过整合归因和不确定性量化,准确地预测地下水储存异常 (GWSA). 这种方法提高了水资源管理中知情决策的可靠性和可解释性.

关键词:
归因分析是一种归因分析.地下水储存异常情况混合深度学习建模模型空间时间异质性 空间时间异质性不确定性量化不确定性的量化.

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