Forecasting Domestic Water Consumption from Smart Meter Readings Using Statistical Methods and Artificial Neural Networks
作者： David Walker , Enrico Creaco , Lydia Vamvakeridou-Lyroudia , Raziyeh Farmani , Zoran Kapelan
DOI: 10.1016/J.PROENG.2015.08.1002
关键词: Simulation 、 Artificial neural network 、 Range (statistics) 、 Consumption (economics) 、 Smart meter 、 Real-time computing 、 Metre 、 Domestic water consumption 、 Engineering
摘要: Abstract This paper presents an artificial neural network-based model of domestic water consumption. The is based on real-world data collected from smart meters, and represents a step toward being able to real-time meter data. A range input schemas are examined, including real readings summary statistics derived readings, it found that the models can predict some consumption but struggle accurately match in cases peak usage.
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