Short-Term Urban Water Demand Prediction Considering Weather Factors-Reference-Cited by-同舟云学术

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Short-Term Urban Water Demand Prediction Considering Weather Factors

Published:2018-08-10 Issue:14 Volume:32 Page:4527-4542
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Zubaidi Salah L.,Gharghan Sadik K.,Dooley Jayne,Alkhaddar Rafid M.,Abdellatif Mawada

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/article/10.1007/s11269-018-2061-y/fulltext.html

Reference35 articles.

1. Adamowski JF (2008) Peak daily water demand forecast modeling using artificial neural networks. J Water Resour Plan Manag 134:119–128

2. Adamowski J, Fung Chan H, Prasher SO, Ozga-Zielinski B, Sliusarieva A (2012) Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada. Water Resour Res 48:1–14

3. Ahmed M, Mohamed A, Homod R, Shareef H (2016) Hybrid LSA-ANN based home energy management scheduling controller for residential demand response strategy. Energies 9:716

4. Ahmed MS, Mohamed A, Khatib T, Shareef H, Homod RZ, Ali JA (2017) Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm. Energy Build 138:215–227

5. ASCE Task Committee (2000) Artificial neural networks in hydrology. I: preliminary concepts. Journal of Hydrologic Egineering. ASCE Task Committee

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