标题： 用于支持水分配网络中人工智能研究的工具箱 显示英文标题

标题： A Toolbox for Supporting Research on AI in Water Distribution Networks

摘要： 饮用水是人类的重要资源，因此，供水管网（WDNs）被视为现代社会的关键基础设施。WDN的运行面临着各种挑战，如水泄漏和污染、网络/物理攻击、泵运行时的高能耗等。由于各种不确定性来源，基于模型的方法已经达到其极限，人工智能方法为这些挑战提供了有前途的解决方案。在本工作中，我们引入了一个Python工具箱，用于复杂场景建模与生成，以便人工智能研究人员可以轻松获取来自饮用水领域的挑战性问题。除了提供一个高级接口，便于生成水力和水质场景数据外，它还提供了对流行事件检测基准的便捷访问以及开发控制算法的环境。 显示英文摘要

摘要： Drinking water is a vital resource for humanity, and thus, Water Distribution Networks (WDNs) are considered critical infrastructures in modern societies. The operation of WDNs is subject to diverse challenges such as water leakages and contamination, cyber/physical attacks, high energy consumption during pump operation, etc. With model-based methods reaching their limits due to various uncertainty sources, AI methods offer promising solutions to those challenges. In this work, we introduce a Python toolbox for complex scenario modeling \& generation such that AI researchers can easily access challenging problems from the drinking water domain. Besides providing a high-level interface for the easy generation of hydraulic and water quality scenario data, it also provides easy access to popular event detection benchmarks and an environment for developing control algorithms.