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Start date: 2010End date: 2019Type: search.filters.itemtype.Conference PaperSubject: search.filters.subject.Signal processingSubject: search.filters.subject.Feature ExtractionAuthor: search.filters.author.Aytekin, Tevfik

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    Short term water demand forecasting using regional data, Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini
    (Institute of Electrical and Electronics Engineers Inc., 2019) Zeynep Yildiz, Tugba; Aytekin, Tevfik; Zeynep Yildiz, Tugba,; Aytekin, Tevfik, Department of Computer Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey
    Limited water resources and changing climatic conditions make water one of the critical natural resources. In order to manage this limited resource in the most effective way, real-time monitoring and automatic control systems are becoming increasingly popular. Water demand forecasting is one of the important subjects in these studies. Accurate water demand forecasting increases efficiency in the management of water networks and also allows for leak/fraud detection. In this work, we carry out short term water demand forecasting using water consumption data collected from water meters in a regional area. For forecasting, we first clean water consumption data, extract various features and apply machine learning methods for forecasting. After giving the experimental results we discuss future improvements. © 2020 Elsevier B.V., All rights reserved.