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Multivariable Time Series Forecasting for Urban Water Demand Based on Temporal Convolutional Network Combining Random Forest Feature Selection and Discrete Wavelet Transform

Crossref DOI link: https://doi.org/10.1007/s11269-022-03207-z

Published Online: 2022-06-14

Published Print: 2022-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Guo, Jun

Sun, Hui

Du, Baigang https://orcid.org/0000-0002-6088-1546
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (51705386)

China Scholarship Council (201606955091)

Fundamental Research Funds for the Central Universities (2018-IVB-010)
License Information

Text and Data Mining valid from 2022-06-14

Version of Record valid from 2022-06-14
More Information

Article History

Received: 27 October 2021

Accepted: 25 May 2022

First Online: 14 June 2022

Declarations

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: Not required as no animal/human was involved in the study.

: Authors agreeing to participate any survey or feedback tasks.

: Authors allow publication if the research is accepted.

: All authors declare that they have no conflict of interest.

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