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深度模糊映射非参数模型用于实时估计水分系统的需求:一个新的视角
Qingzhou Zhang1, Jingzhi Yang2, Weiping Zhang3
1Key Laboratory of Green Construction and Intelligent Maintenance for Civil Engineering of Hebei Province, Hebei Province Low-Carbon and Clean Building Heating Technology Innovation Center, Yanshan University, Qinhuangdao 066004, China.
Water research
|June 4, 2023
概括
本研究引入了一种新的深度模糊映射 (DFM) 模型,用于实时水分系统 (WDS) 校准. DFM模型准确地估计了节点的水消耗效率,优于传统方法.
科学领域:
- 液压工程 液压工程 液压工程
- 水资源管理 水资源管理
- 在土木工程中的人工智能.
背景情况:
- 水分系统 (WDS) 需要实时校准,以实现高效的设计,操作和管理.
- 城市基础设施信息化日益增长,需要准确高效的WDS在线校准,特别是对于大型和复杂的系统.
研究的目的:
- 为实时WDS建模提出一种新的深度模糊映射 (DFM) 非参数模型.
- 从传感器数据到节点用水量建立精确的反向映射,使用模糊逻辑结合不确定性.
- 开发一个计算效率高,准确的WDS校准方法.
主要方法:
- 开发了一个深度模糊映射 (DFM) 非参数模型框架.
- 利用模糊的会员功能来解决WDS建模中的不确定性.
- 从传感器数据到节点用水量的精确反向映射获得了分析解决方案.
- 应用了DFM方法对两个案例研究进行验证.
主要成果:
- DFM模型提供了节点用水量的实时估计.
- 与传统校准方法相比,实现了更高的准确性和计算效率.
- 在WDS建模和校准中表现出稳健性.
结论:
- DFM方法在实时WDS校准中提供了显著的进步.
- 该方法有效地处理不确定性,并提供准确,高效和可靠的估计.
- 这种新的方法满足了对WDSs实时细粒度控制的日益增长的需求.
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