You are not logged in.

A neural network-GARCH-based method for construction of prediction intervals

Khosravi, Abbas, Nahavandi, Saeid and Creighton, Doug 2013, A neural network-GARCH-based method for construction of prediction intervals, Electric power systems research, vol. 96, pp. 185-193, doi: 10.1016/j.epsr.2012.11.007.

Attached Files
Name Description MIMEType Size Downloads

Title A neural network-GARCH-based method for construction of prediction intervals
Author(s) Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Creighton, DougORCID iD for Creighton, Doug orcid.org/0000-0002-9217-1231
Journal name Electric power systems research
Volume number 96
Start page 185
End page 193
Total pages 9
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2013-03
ISSN 0378-7796
1873-2046
Keyword(s) electricity price
prediction intervals
neural networks
GARCH
bootstrap
Language eng
DOI 10.1016/j.epsr.2012.11.007
Field of Research 080110 Simulation and Modelling
Socio Economic Objective 850699 Energy Storage, Distribution and Supply not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050990

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 25 times in TR Web of Science
Scopus Citation Count Cited 31 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 285 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Tue, 05 Mar 2013, 15:17:35 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.