An intelligent hybrid short-term load forecasting model for smart power grids Raza, Muhammad Qamar, Nadarajah, Mithulananthan, Duong, Quoc Hung and Baharudin, Zuhairi 2017, An intelligent hybrid short-term load forecasting model for smart power grids, Sustainable Cities and Society, vol. 31, pp. 264-275, doi: 10.1016/j.scs.2016.12.006. Attached Files Name Description MIMEType Size Downloads Title An intelligent hybrid short-term load forecasting model for smart power grids Author(s) Raza, Muhammad Qamar Nadarajah, Mithulananthan Duong, Quoc Hung orcid.org/0000-0002-7767-6821 Baharudin, Zuhairi Journal name Sustainable Cities and Society Volume number 31 Start page 264 End page 275 Total pages 12 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2017-05-01 ISSN 2210-6707 2210-6715 Keyword(s) science & technology technology construction & building technology greet & sustainable science & technology energy & fuels short-term load forecasting (STLF) artificial neural network ( ANN) global best particle swarm optimization (GPSO) back propagation (BP) Levenberg marquardt (LM) meteorological and exogenous variables mean absolute percentage error (MAPE) neural-network algorithm Language eng DOI 10.1016/j.scs.2016.12.006 HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2016, Elsevier Persistent URL http://hdl.handle.net/10536/DRO/DU:30106610 Document type: Journal Article Collection: School of Engineering Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 02 Mar 2018, 14:37:21 EST Fri, 02 Mar 2018, 14:37:51 EST Sat, 03 Mar 2018, 04:00:32 EST Sat, 03 Mar 2018, 05:06:28 EST Mon, 12 Mar 2018, 09:49:58 EST Mon, 12 Mar 2018, 09:53:47 EST Filtered Full Citation counts:   Cited 5 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 10 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Fri, 02 Mar 2018, 14:37:51 EST

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