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Interval type-2 intuitionistic fuzzy logic system for non-linear system prediction

Eyoh, Imo; John, Robert; de Maere, Geert

Authors

Imo Eyoh

Robert John robert.john@nottingham.ac.uk



Abstract

This paper presents an approach to prediction based on a new interval type-2 intuitionistic fuzzy logic system (IT2IFLS) of Takagi-Sugeno-Kang (TSK) fuzzy inference. The gradient descent algorithm (GDA) is used to adapt the parame- ters of the IT2IFLS. The empirical comparison is made on the designed system using two synthetic datasets. Analysis of our results reveal that the presence of additional degrees of freedom in terms of non-membership functions and hesitation indexes in IT2IFLS tend to reduce the root mean square error (RMSE) of the system compared to a type-1 fuzzy logic approach and some interval type-2 fuzzy systems.

Publication Date Oct 11, 2016
Peer Reviewed Peer Reviewed
APA6 Citation Eyoh, I., John, R., & de Maere, G. (2016). Interval type-2 intuitionistic fuzzy logic system for non-linear system prediction
Related Public URLs http://www.smc2016.org/
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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IT2IFLS1.pdf (284 Kb)
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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