Prediction of Minimum Night Flow for Enhancing Leakage Detection Capabilities in Water Distribution Networks

In South Korea, a water supply enhancement project is being carried out to preemptively respond drought and loss by reducing pipeline leakages supplying stable tap through the maintenance of an aging network. order reduce leakage, District Metered Area (DMA) was established monitor predict minimum night flow based on data collected from IoT sensors. this study, model Multi-Layer Perceptron (MLP) Long Short-Term Memory (LSTM) constructed MNF (minimum flow) County Y. The prediction results compared with MLP networks LSTM model. outcome showed that LSTM-MNF proposed in study performed better than MLP-MNF Therefore, research methods can contribute technical support for leakage reductions responding expected increase at night.