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Updated: Jun 14, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

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在数据稀缺地区的河流盐度预测:应用转移学习和不确定性量化

Kasra Khodkar1, Ali Mirchi1, Vahid Nourani2

  • 1Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK 74078, USA.

Journal of contaminant hydrology
|September 1, 2024
PubMed
概括

本研究提出了一个转移学习框架,用于生成连续的每日流盐度估计,改善数据稀缺地区的水资源管理. 该方法可靠地使用神经网络预测盐度,量化不确定性.

关键词:
下限上限估计 (LUBE) 的下限上限估计机器学习是机器学习.缺少的数据数据.河流的盐度 河流的盐度不确定性量化不确定性的量化.上红河流域的红河流域.

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