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Prediction of water consumption using Artificial Neural Networks modelling (ANN)

机译:使用人工神经网络模型(ANN)预测用水量

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This paper presents an application of Artificial Neural Network models (ANN) to predict the water consumption at two scales: i) District Metered Area (DMA) located in the Scientific Campus of Lille University and ii) End user representing a restaurant inside this DMA. Data are collected from Automated Meter Readers (AMRs) that measure in near real-time the water consumption. The models are trained at both daily and hourly time intervals using historical values and the variation between the hour and the type of days. The paper shows that the ANN-based models can well predict the water consumption including peak values.
机译:本文介绍了人工神经网络模型(ANN)在两个尺度上预测用水量的应用:i)位于里尔大学科学园区的地区计量区域(DMA),以及ii)代表该DMA内部餐厅的最终用户。数据是从自动抄表器(AMR)收集的,可以近乎实时地测量用水量。使用历史值以及小时和天类型之间的变化,以每天和每小时的时间间隔训练模型。本文表明,基于ANN的模型可以很好地预测包括峰值在内的耗水量。

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