An ensemble stacked model with bias correction for improved water demand forecasting
Author:
Affiliation:
1. Centre for Water Systems, University of Exeter, Exeter, UK
2. Department of Water Management., Delft University of Technology, Delft, Netherlands
Funder
Engineering and Physical Sciences Research Council
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2020.1758164
Reference65 articles.
1. Peak Daily Water Demand Forecast Modeling Using Artificial Neural Networks
2. Monthly water demand prediction using wavelet transform, first-order differencing and linear detrending techniques based on multilayer perceptron models
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4. A multi-scale relevance vector regression approach for daily urban water demand forecasting
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