A hybrid FMM-CART model for human activity recognition Seera, Manjeevan, Loo, Chu Kiong and Lim, Chee Peng 2014, A hybrid FMM-CART model for human activity recognition, in IEEE 2014 : Proceedings of the International Conference on Systems, Man and Cybernetics (SMC), IEEE, Piscataway, N.J., pp. 182-187, doi: 10.1109/SMC.2014.6973904. Attached Files Name Description MIMEType Size Downloads Title A hybrid FMM-CART model for human activity recognition Author(s) Seera, Manjeevan Loo, Chu Kiong Lim, Chee Peng orcid.org/0000-0003-4191-9083 Conference name Systems, Man and Cybernetics (SMC). IEEE International Conference (2014 : San Diego, Calif.) Conference location San Diego, Calif. Conference dates 2014/10/05 - 2014/10/08 Title of proceedings IEEE 2014 : Proceedings of the International Conference on Systems, Man and Cybernetics (SMC) Publication date 2014 Series Systems, Man and Cybernetics (SMC) Start page 182 End page 187 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) classification and regression tree fuzzy min-max neural network human activity recognition rule extraction Summary In this paper, the application of a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) to human activity recognition is presented. The hybrid FMM-CART model capitalizes the merits of both FMM and CART in data classification and rule extraction. To evaluate the effectiveness of FMM-CART, two data sets related to human activity recognition problems are conducted. The results obtained are higher than those reported in the literature. More importantly, practical rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM- CART. This outcome positively indicates the potential of FMM- CART in undertaking human activity recognition tasks. ISSN 1062-922X Language eng DOI 10.1109/SMC.2014.6973904 Field of Research 080108 Neural, Evolutionary and Fuzzy Computation Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2014, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30076124 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system 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 Fri, 21 Aug 2015, 11:28:46 EST Sat, 22 Aug 2015, 05:04:33 EST Mon, 24 Aug 2015, 08:13:55 EST Tue, 17 May 2016, 12:57:13 EST Wed, 18 May 2016, 06:22:22 EST Fri, 07 Oct 2016, 10:44:46 EST Fri, 07 Oct 2016, 11:00:27 EST Fri, 07 Oct 2016, 11:03:11 EST Sat, 22 Jan 2022, 01:31:54 EST Filtered Full Citation counts:   Cited 6 times in TR Web of Science Cited 9 times in Scopus Search Google Scholar Access Statistics: 383 Abstract Views, 3 File Downloads  -  Detailed Statistics Created: Tue, 17 May 2016, 12:57:13 EST