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Using artificial neural network models to assess water quality in water distribution networks

机译:利用人工神经网络模型评估水分分配网络中的水质

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The purpose of the research is to assess chlorine concentration in WDS using statistical models based on ANN in combination with Monte-Carlo. This approach offers advantages in contrast to the generally use methods for modeling of chlorine decay in drinking water systems until now. The model was tested on one specific location using the hydraulic and water quality parameters such as flow, pH, temperature, etc. The model allows forecasting chlorine concentration at selected nodes of the water supply system. The results obtained in these selected nodes allow then to compare the chlorine concentration with EPANET in the system under assessment.
机译:该研究的目的是使用基于ANN的统计模型与Monte-Carlo组合使用统计模型来评估WD中的氯浓度。这种方法与普遍使用方法与饮用水系统中的氯衰减建模的普遍用途相比,提供了相反的优点。使用液压和水质参数如流动,pH,温度等进行一个特定位置测试该模型。该模型允许在供水系统的选定节点处预测氯浓度。然后,在这些所选节点中获得的结果允许在评估下将氯浓度与系统中的EPANET进行比较。

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