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 PengORCID iD for 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: Centre for Intelligent Systems Research
GTP 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 0 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 215 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Tue, 17 May 2016, 12:57:13 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.