Constructing optimal prediction intervals by using neural networks and bootstrap method Khosravi, Abbas, Nahavandi, Saeid, Srinivasan, Dipti and Khosravi, Rihanna 2015, Constructing optimal prediction intervals by using neural networks and bootstrap method, IEEE Transactions on neural networks and learning systems, vol. 26, no. 8, pp. 1810-1815, doi: 10.1109/TNNLS.2014.2354418. Attached Files Name Description MIMEType Size Downloads Title Constructing optimal prediction intervals by using neural networks and bootstrap method Author(s) Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Srinivasan, Dipti Khosravi, Rihanna Journal name IEEE Transactions on neural networks and learning systems Volume number 26 Issue number 8 Start page 1810 End page 1815 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Publication date 2015-08-08 ISSN 2162-2388 Keyword(s) Bootstrap uncertainty quantification Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Hardware & Architecture Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering LOAD OPTIMIZATION Summary This brief proposes an efficient technique for the construction of optimized prediction intervals (PIs) by using the bootstrap technique. The method employs an innovative PI-based cost function in the training of neural networks (NNs) used for estimation of the target variance in the bootstrap method. An optimization algorithm is developed for minimization of the cost function and adjustment of NN parameters. The performance of the optimized bootstrap method is examined for seven synthetic and real-world case studies. It is shown that application of the proposed method improves the quality of constructed PIs by more than 28% over the existing technique, leading to narrower PIs with a coverage probability greater than the nominal confidence level. Language eng DOI 10.1109/TNNLS.2014.2354418 Field of Research 080108 Neural, Evolutionary and Fuzzy Computation Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2015, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30076648 Document type: Journal Article Collections: Institute for Intelligent Systems Research and Innovation (IISRI) 2018 ERA Submission GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges   Author URL 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, 25 Aug 2015, 14:40:34 EST Wed, 26 Aug 2015, 05:05:17 EST Wed, 26 Aug 2015, 08:14:38 EST Wed, 26 Aug 2015, 08:20:57 EST Wed, 26 Aug 2015, 08:58:38 EST Thu, 27 Aug 2015, 06:09:29 EST Thu, 27 Aug 2015, 15:27:05 EST Thu, 27 Aug 2015, 15:28:11 EST Thu, 27 Aug 2015, 15:29:26 EST Filtered Full Citation counts:   Cited 21 times in TR Web of Science Cited 24 times in Scopus Search Google Scholar Access Statistics: 552 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Wed, 26 Aug 2015, 08:58:38 EST

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