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制造浪潮:城市水资源建模中的知识和数据融合
Haoran Duan1,2, Jiuling Li1, Zhiguo Yuan3,4
1The Australian Centre for Water and Environmental Biotechnology (ACWEB), The University of Queensland, St. Lucia, QLD, Australia.
Water research X
|August 7, 2024
概括
本研究建议将机械学知识与城市水系统 (UWS) 的数据驱动模型相结合. 这种基于知识的方法提高了可解释性,并减少了对更好的UWS管理的数据需求.
科学领域:
- 环境工程 环境工程
- 计算机科学 计算机科学
- 系统科学 系统科学
背景情况:
- 机械模型是城市水系统 (UWS) 的基础,但面临复杂性和计算需求的挑战.
- 数据驱动模型为UWS提供了潜力,但受解释性和数据可用性限制.
- 目前的UWS建模努力平衡准确性,效率和可解释性.
研究的目的:
- 倡导在UWS.WS中转向以知识为基础的数据驱动建模的范式转变.
- 提出一个概念框架,将机械学知识整合到数据驱动的UWS模型中.
- 突出这种综合方法对UWS管理的好处.
主要方法:
- 通过先进的数据驱动技术,利用丰富的传感器数据.
- 将现有的机械知识集成到数据驱动的模型框架中.
- 在UWS中开发知识为基础的建模的概念框架.
主要成果:
- 基于知识的模型减少了数据需求,提高了可解释性.
- 综合方法提供了更准确的UWS动态的表示.
- 这种方法提高了效率,并解决了UWS建模中的不确定性.
结论:
- 以知识为基础的数据驱动的建模方法对于推进UWS管理至关重要.
- 这种范式的转变使得UWS建模更加高效,可解释和准确.
- 拟议的框架支持在UWS运营的数字时代改善决策.
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