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Updated: Jul 20, 2025

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基于人工智能方法的悬浮沉积物负载预测建模:热带地区作为一个案例研究

Mohammed Falah Allawi1, Sadeq Oleiwi Sulaiman1, Khamis Naba Sayl1

  • 1Dams and Water Resources Engineering Department, College of Engineering, University Of Anbar, Ramadi, Iraq.

Heliyon
|July 31, 2023
PubMed
概括

准确的悬浮沉积物负载 (SSL) 预测对于水资源管理至关重要. 一个新的长期短期存储器 (LSTM) 模型显著提高了在柔佛河的SSL预测准确性,为环境规划提供了可靠的工具.

关键词:
人工智能的人工智能是人工智能.在 LSTM 模型中.预测模型的预测模型.沉积 沉积 沉积 沉积 沉积热带地区是一个热带地区.

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