Comments: Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia

Accurate prediction of short-term water demand, especially, in the case of extreme weather conditions such as flood, droughts and storms, is crucial information for the policy makers to manage the availability of freshwater. This study develops a hybrid model for the prediction of monthly water dema...

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Bibliographic Details
Main Authors:	Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.
Other Authors:	57201458677
Format:	Article
Published:	Springer Science and Business Media Deutschland GmbH 2024
Subjects:	Adaptive guided differential evolution algorithm Eleven learning algorithms Hybrid model Monthly water demand Australia Melbourne Victoria [Australia] Discrete wavelet transforms Evaporation Evapotranspiration Evolutionary algorithms Mean square error Meteorology Optimization Principal component analysis Water supply Weather forecasting Demand prediction Differential evolution algorithms Eleven learning algorithm Extreme weather conditions Water demand accuracy assessment adaptive management algorithm artificial neural network climate conditions database extreme event prediction water demand water use Learning algorithms
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia

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