The applicability of Generic Self-Evolving Takagi-Sugeno-Kang neuro-fuzzy model in modeling rainfall-runoff and river routing Ashrafi, Mohammad, Chua, Lloyd HC and Quek, Chai 2019, The applicability of Generic Self-Evolving Takagi-Sugeno-Kang neuro-fuzzy model in modeling rainfall-runoff and river routing, Hydrology research, vol. 50, no. 4, pp. 991-1001, doi: 10.2166/nh.2019.146. Title The applicability of Generic Self-Evolving Takagi-Sugeno-Kang neuro-fuzzy model in modeling rainfall-runoff and river routing Author(s) Ashrafi, Mohammad Chua, Lloyd HC orcid.org/0000-0003-2523-3735 Quek, Chai Journal name Hydrology research Volume number 50 Issue number 4 Start page 991 End page 1001 Total pages 11 Publisher IWA Publishing Place of publication London, Eng. Publication date 2019-08-01 ISSN 1998-9563 2224-7955 Keyword(s) GSETSK local learning neuro-fuzzy rainfall–runoff river routing rule base Language eng DOI 10.2166/nh.2019.146 Indigenous content off HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2019, IWA Publishing Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30128784 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Engineering Open Access Collection Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Fri, 09 Aug 2019, 08:52:56 EST Sat, 10 Aug 2019, 05:01:47 EST Tue, 27 Aug 2019, 06:02:32 EST Wed, 28 Aug 2019, 12:16:26 EST Wed, 28 Aug 2019, 12:17:42 EST Fri, 15 Nov 2019, 21:40:26 EST Sun, 28 Feb 2021, 11:36:00 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 4 times in Scopus Search Google Scholar Access Statistics: 167 Abstract Views  -  Detailed Statistics Created: Fri, 09 Aug 2019, 08:52:56 EST

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