Water demand forecasting using extreme learning machines

Water demand forecasting using extreme learning machines

The capacity of recently-developed extreme learning machine (ELM) modelling approaches in forecasting daily urban water demand from limited data, alone or in concert with wavelet analysis (W) or bootstrap (B) methods (i.e., ELM, ELMW, ELMB), was assessed, and compared to that of equivalent tradition...

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Bibliografiska uppgifter
Huvudupphovsmän: Tiwari Mukesh, Adamowski Jan, Adamowski Kazimierz
Materialtyp: Artikel
Språk:English
Publicerad: Polish Academy of Sciences 2016-03-01
Serie:Journal of Water and Land Development
Ämnen:
artificial neural networks
bootstrap
Canada
extreme learning machines
uncertainty
water demand forecasting
wavelets
Länkar:http://www.degruyter.com/view/j/jwld.2016.28.issue-1/jwld-2016-0004/jwld-2016-0004.xml?format=INT

Internet

http://www.degruyter.com/view/j/jwld.2016.28.issue-1/jwld-2016-0004/jwld-2016-0004.xml?format=INT

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