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Updated: Jul 17, 2025

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通过使用标准降水指数和标准水位指数的机器学习算法对干旱条件的评估和预测 (案例研究:伊朗雅兹德省)

Reza Shakeri1, Hossein Amini2, Farshid Fakheri1

  • 1Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran.

Environmental science and pollution research international
|September 1, 2023
PubMed
概括

雅兹德省面临着气象干旱的恶化,水文干旱更严重是由于地下水过度提取而不是降雨不足. 机器学习模型准确地预测了干旱状况,突出了迫切需要水资源管理策略的需求.

关键词:
干旱监测 干旱监测 干旱监测地下水的地下水.机器学习是机器学习.回归是一种回归.这是一个SPI SPI.这就是SWI SWI.水资源 水资源 水资源

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