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Updated: Sep 14, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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通过使用集体分解模型预测月度河流水位

Chaitanya Baliram Pande1,2,3, Lariyah Mohd Sidek4, Bijay Halder5

  • 1Institute of Energy Infrastructure, Universiti Tenaga Nasional, 43000, Kajang, Malaysia. chaitanay45@gmail.com.

Scientific reports
|July 24, 2025
PubMed
概括

本研究介绍了一种混合模型,将完整集体实证模式分解与自适应噪声 (CEEMDAN) 和机器学习相结合,用于准确的河流水位预测. CEEMDAN-RF模型表现出卓越的性能,增强了用于可持续水资源管理的水文预测.

关键词:
人工智能的人工智能是人工智能.数据分解数据的分解.能量 能量 能量 能量 能量穆尔河是穆尔河的一条河流.绩效评估是指进行绩效评估.河流水位水位的水位.可持续发展目标 可持续发展目标

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