Interpretable AI for Short-Term Water Demand Forecasting

Machine learning models such as artificial neural networks (ANNs) are becoming increasingly popular in short-term water demand forecasting. This is because, despite their lack of interpretability, ANNs are able to capture complex interactions between explanatory variables and water consumption bette...

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Bibliografiske detaljer

Principais autores:	Aly-Joy Ulusoy, Carlos Jara-Arriagada, Yuanyang Liu, Bradley Jenks, Ivan Stoianov
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-09-01
Serier:	Engineering Proceedings
Fag:	interpretable machine learning optimal trees water demand forecasting
Online adgang:	https://www.mdpi.com/2673-4591/69/1/101
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