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Case-based reasoning to support decision making for managing drinking water quality events in distribution systems

机译:基于案例的推理,以支持管理配水系统饮用水质量事件的决策

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摘要

In order to better leverage past experience of water quality incidents, and to tap into the unique incident database currently being maintained and required by regulatory authorities, a data mining approach is herein proposed. The quality of drinking water is paramount to protecting public health. However water quality failures do occur, with some of the hardest to understand and manage occurring within distribution systems. In the UK, a regulatory process is applied in which water service providers must report on significant water quality incidents, their causes, actions and outcomes. These reports form a valuable resource that can be explored for improved understanding, to help with future incident management and evaluate potential solutions. Case-based reasoning is a knowledge-based problem-solving technique that relies on the reuse of past experience. The WaterQualityCBR software system presented here was developed as such a decision support tool to more effectively manage water quality in distribution systems.
机译:为了更好地利用过去的水质事故经验,并利用监管机构当前维护和要求的唯一事故数据库,本文提出了一种数据挖掘方法。饮用水的质量对保护公众健康至关重要。但是,水质确实会发生故障,其中一些最难以理解和管理的故障是在配电系统内发生的。在英国,实行了监管程序,其中水服务提供者必须报告重大水质事件,其原因,行动和结果。这些报告构成了宝贵的资源,可以进行探索以增进了解,以帮助将来的事件管理和评估潜在的解决方案。基于案例的推理是一种基于知识的问题解决技术,它依赖于对过去经验的重用。此处介绍的WaterQualityCBR软件系统是作为这样的决策支持工具而开发的,可以更有效地管理分配系统中的水质。

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