Open AccessA machine learning framework for predicting downstream water end-use events with upstream sensors
Author(s) -
Ian Kropp,
A. Pouyan Nejadhashemi,
Ryan Julien,
Jade Mitchell,
Andrew J. Whelton
Publication year - 2022
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2022.226
Subject(s) - downstream (manufacturing) , upstream (networking) , upstream and downstream (dna) , overfitting , computer science , machine learning , preprocessor , bottleneck , artificial intelligence , data pre processing , data mining , engineering , artificial neural network , embedded system , computer network , operations management
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