Machine learning method is an alternative for the hydrological model in an alpine catchment in the Tianshan region, Central Asia

Overview of attention for article published in Journal of Hydrology: Regional Studies, October 2023

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In the top 25% of all research outputs scored by Altmetric
Among the highest-scoring outputs from this source (#47 of 494)
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研究揭示机器学习方法可较好地模拟天山高海拔流域日流量和极端流量

Chinese Academy of Science, 16 Aug 2023

中亚天山高海拔地区的复杂地形和恶劣天气条件以及稀少的水文气象站点分布，导致该地区气象和水文观测数据缺乏。而传统的基于物理过程的水文模型需要大量的观测数据来校准空间参数，使得高山区分布式水文模拟颇为困难。机器学习方法（LSTM）由于非线性拟合能力强大而逐渐被应…

LSTM可以较好地模拟天山高海拔流域日流量和极端流量

Ebiotrade, 15 Aug 2023

【字体：大中小】时间：2023年08月15日来源：中国科学院新疆生态与地理研究所编辑推荐：相关成果以“Machine learning method is an alternative for the hydrological model…

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