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Hybrid model for the training of interval type-2 fuzzy logic system

Hassan, Saima, Khosravi, Abbas, Jaafar, Jafreezal and Khanesar, Mojtaba Ahmadieh 2015, Hybrid model for the training of interval type-2 fuzzy logic system, in ICONIP 2015 : Neural Information Processing Proceedings Part I, Springer, Cham, Switzerland, pp. 644-653, doi: 10.1007/978-3-319-26532-2_71.

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Title Hybrid model for the training of interval type-2 fuzzy logic system
Author(s) Hassan, Saima
Khosravi, Abbas
Jaafar, Jafreezal
Khanesar, Mojtaba Ahmadieh
Conference name Neural Information Processing. International Conference (22nd : 2015 : Istanbul, Turkey)
Conference location Istanbul, Turkey
Conference dates 9-12 Nov. 2015
Title of proceedings ICONIP 2015 : Neural Information Processing Proceedings Part I
Publication date 2015
Series Lecture notes in computer science
Start page 644
End page 653
Total pages 10
Publisher Springer
Place of publication Cham, Switzerland
Keyword(s) hybrid learning model
extreme learning machine
genetic algorithm
interval type-2 fuzzy logic system
predicition
Summary In this paper, a hybrid training model for interval type-2 fuzzy logic system is proposed. The hybrid training model uses extreme learning machine to tune the consequent part parameters and genetic algorithm to optimize the antecedent part parameters. The proposed hybrid learning model of interval type-2 fuzzy logic system is tested on the prediction of Mackey-Glass time series data sets with different levels of noise. The results are compared with the existing models in literature; extreme learning machine and Kalman filter based learning of consequent part parameters with randomly generated antecedent part parameters. It is observed that the interval type-2 fuzzy logic system provides improved performance with the proposed hybrid learning model.
ISBN 9783319265315
ISSN 0302-9743
1611-3349
Language eng
DOI 10.1007/978-3-319-26532-2_71
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 ©2015, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082497

Document type: Conference Paper
Collections: Centre for Intelligent Systems Research
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