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Updated: May 30, 2025

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

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三种机器学习模型在预测每日流量和不确定性评估方面的有效性

Luka Vinokić1, Milan Dotlić1, Veljko Prodanović1,2

  • 1Institute for Artificial Intelligence R&D of Serbia, Fruškogorska 1, Novi Sad 21000, Serbia.

Water research X
|January 27, 2025
PubMed
概括

时间科尔莫戈罗夫-阿诺德网络 (TKAN) 在流量预测方面表现强,性能优于长短期内存 (LSTM) 并且几乎与时间卷积网络 (TCN) 相匹配. 这项研究提高了机器学习模型的可靠性,用于自适应式水资源管理.

关键词:
机器学习 机器学习流的流量 流的流量这就是TKAN TKAN.时间序列预测时间序列预测不确定性 不确定性

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