Short term load forecasting using interval type-2 fuzzy logic systems Khosravi, Abbas, Nahavandi, Saeid and Creighton, Doug 2011, Short term load forecasting using interval type-2 fuzzy logic systems, in FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems, IEEE, Piscataway, N. J., pp. 502-508. Attached Files Name Description MIMEType Size Downloads Title Short term load forecasting using interval type-2 fuzzy logic systems Author(s) Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Creighton, Doug orcid.org/0000-0002-9217-1231 Conference name International Conference on Fuzzy Systems (2011 : Taipei, Taiwan) Conference location Taipei, Taiwan Conference dates 27-30 Jun. 2011 Title of proceedings FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems Editor(s) [Unknown] Publication date 2011 Conference series IEEE International Conference on Fuzzy Systems Start page 502 End page 508 Total pages 7 Publisher IEEE Place of publication Piscataway, N. J. Keyword(s) load forecasting type-2 fuzzy logic Summary Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy may drop due to presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. This paper proposes the application of Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) for the problem of STLF. IT2 FLSs, with extra degrees of freedom, are an excellent tool for handling prevailing uncertainties and improving the prediction accuracy. Experiments conducted with real datasets show that IT2 FLS models appropriately approximate future load demands with an acceptable accuracy. Furthermore, they demonstrate an encouraging degree of accuracy superior to feedforward neural networks used in this study. ISBN 1424473160 9781424473168 ISSN 1098-7584 Language eng Field of Research 080108 Neural, Evolutionary and Fuzzy Computation 090607 Power and Energy Systems Engineering (excl Renewable Power) Socio Economic Objective 850601 Energy Services and Utilities HERDC Research category E1 Full written paper - refereed Copyright notice ©2011, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30044774 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) 2018 ERA Submission GTP Research Related Links Link Description Connect to published version (restricted access) 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 Tue, 01 May 2012, 10:57:14 EST Wed, 02 May 2012, 15:43:03 EST Wed, 02 May 2012, 15:44:53 EST Mon, 14 May 2012, 10:35:24 EST Mon, 14 May 2012, 11:12:15 EST Mon, 14 May 2012, 11:12:58 EST Mon, 14 May 2012, 11:13:59 EST Tue, 15 May 2012, 09:18:00 EST Wed, 02 Jul 2014, 15:44:23 EST Wed, 06 Aug 2014, 15:50:36 EST Fri, 17 Oct 2014, 11:30:54 EST Wed, 21 Oct 2015, 17:42:13 EST Filtered Full Citation counts:   Cited 22 times in TR Web of Science Cited 26 times in Scopus Search Google Scholar Access Statistics: 743 Abstract Views, 11 File Downloads  -  Detailed Statistics Created: Tue, 01 May 2012, 10:57:14 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.