Fault detection and diagnosis using the fuzzy min-max neural network with rule extraction Chen, KY, Lim, Chee Peng and Lai, WK 2004, Fault detection and diagnosis using the fuzzy min-max neural network with rule extraction, in KES: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, Springer Verlag, Berlin, Germany, pp. 357-364, doi: 10.1007/978-3-540-30134-9_48. Title Fault detection and diagnosis using the fuzzy min-max neural network with rule extraction Author(s) Chen, KY Lim, Chee Peng orcid.org/0000-0003-4191-9083 Lai, WK Conference location Wellington, New Zealand Conference dates 2004/09/20 - 2004/09/25 Title of proceedings KES: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems Publication date 2004 Start page 357 End page 364 Total pages 8 Publisher Springer Verlag Place of publication Berlin, Germany Keyword(s) Fuzzy Min-Max neural network (FMM) “black-box” phenomenon Circulating Water (CW) system domain Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Information Systems Computer Science ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-540-30134-9_48 Field of Research 08 Information And Computing Sciences HERDC Research category EN.1 Other conference paper Copyright notice ©2004, Springer-Verlag Berlin Heidelberg Persistent URL http://hdl.handle.net/10536/DRO/DU:30099612 Document type: Conference Paper Collection: Centre for Intelligent Systems Research Related Links Link Description   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 26 Jul 2017, 12:10:17 EST Thu, 27 Jul 2017, 05:10:55 EST Thu, 27 Jul 2017, 06:09:29 EST Sat, 21 Oct 2017, 02:04:48 EST Mon, 02 Jul 2018, 08:40:29 EST Mon, 02 Jul 2018, 08:44:33 EST Mon, 02 Jul 2018, 08:45:22 EST Mon, 02 Jul 2018, 08:45:57 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 13 Abstract Views  -  Detailed Statistics Created: Wed, 26 Jul 2017, 12:10:17 EST

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