Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/2984
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGooi, Hoay Beng.en_US
dc.date.accessioned2008-09-17T09:18:14Z-
dc.date.available2008-09-17T09:18:14Z-
dc.date.copyright1998en_US
dc.date.issued1998-
dc.identifier.urihttp://hdl.handle.net/10356/2984-
dc.description.abstractThis project examines the usefulness of ANN techniques using load and forecasting data supplied from the Public Utilities Board of Singapore.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems-
dc.titleAdaptive short-term load forecasting using artificial neural networksen_US
dc.typeResearch Reporten_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
Appears in Collections:EEE Research Reports (Staff & Graduate Students)
Files in This Item:
File Description SizeFormat 
EEE-RESEARCH-REPORT_44.pdf
  Restricted Access
968.5 kBAdobe PDFView/Open

Page view(s) 50

398
Updated on May 17, 2021

Download(s) 50

17
Updated on May 17, 2021

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.