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Evaluation of WWTP discharges into a Mediterranean river using KSOM neural networks and mass balance modelling

机译:利用KSOM神经网络和质量平衡模型评价WWTP排放到地中海河流中

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摘要

The water quality of the Tet River, referred to nutrients compounds, is lower than the expected. Its management must be largely improved. The present work takes part in a global effort of development and evaluation of reliable and robust tools, with the aim of allowing the control and supervision of its lowland area (at the south Mediterranean coast of France). A simplified model, based on mass balances, has been developed to estimate nitrogen and organic matter concentrations in the stream and to describe the river water quality. Kohonen self-organizing maps (KSOMs) were used to deal with missing data. This kind of neural networks proved to be very useful to predict missing components and to complete the available database, describing the chemical quality of the river and the Wastewater Treatment Plant (WWTP) outflows. The simulation model also proved to be a good tool for the system evaluated. The results it provided reveal the high impact of the WWTPs located along the studied area, due to malfunction and tourism activities.
机译:特特河的水质(指营养成分)低于预期。必须大大改善其管理。目前的工作是在全球范围内努力开发和评估可靠且可靠的工具,目的是允许对其低地地区(法国南部地中海沿岸)进行控制和监督。已开发出一种基于质量平衡的简化模型,以估算河流中的氮和有机物浓度并描述河流水质。 Kohonen自组织图(KSOM)用于处理丢失的数据。事实证明,这种神经网络对于预测缺少的成分并完成可用的数据库非常有用,该数据库描述了河流和废水处理厂(WWTP)流出物的化学质量。仿真模型也被证明是评估系统的良好工具。它提供的结果表明,由于故障和旅游活动,沿研究区域坐落的污水处理厂的巨大影响。

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