Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1186/s13104-024-06878-6.pdf
Reference28 articles.
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3. Wang X-j, et al. Adaptation to climate change impacts on water demand. Mitig Adapt Strat Glob Change. 2016;21:81–99.
4. Hamidi O, Abbasi H, Mirhashemi H. Analysis of the Response of Urban Water Consumption to climatic variables: Case Study of Khorramabad City in Iran. Adv Meteorol. 2021;2021:1–14.
5. Chaplot B. Prediction of rainfall time series using soft computing techniques. Environ Monit Assess. 2021;193(11):721.
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