A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning

A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning

This study presents a collaborative framework developed by the Water Futures team of researchers for the “Battle of the Water Demand Forecasting” challenge at the 3rd International WDSA-CCWI Joint Conference. The framework integrates an ensemble of machine learning forecasting models into a determin...

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Bibliographic Details
Main Authors: Dennis Zanutto, Christos Michalopoulos, Georgios-Alexandros Chatzistefanou, Lydia Vamvakeridou-Lyroudia, Lydia Tsiami, Konstantinos Glynis, Panagiotis Samartzis, Luca Hermes, Fabian Hinder, Jonas Vaquet, Valerie Vaquet, Demetrios Eliades, Marios Polycarpou, Phoebe Koundouri, Barbara Hammer, Dragan Savić
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Engineering Proceedings
Subjects:
machine learning
ensemble forecasting
water demand forecasting
district metered areas
deep learning
Online Access:https://www.mdpi.com/2673-4591/69/1/60
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