NDLI: A computationally fast Interval Type-2 Neuro-Fuzzy Inference System and its Meta-Cognitive projection based learning algorithm

Content Provider	IEEE Xplore Digital Library
Author	Das, A.K. Subramanian, K. Suresh, S.
Copyright Year	2014
Description	Author affiliation: Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore (Das, A.K.; Subramanian, K.; Suresh, S.)
Abstract	In this paper, a computationally efficient Interval Type-2 Neuro-Fuzzy Inference System (IT2FIS) and its Meta-Cognitive projection based learning (PBL) algorithm is presented, together referred as PBL-McIT2FIS. A six layered network with computationally cheap type-reduction technique is proposed, rendering the inference mechanism faster. During learning, the projection based learning algorithm assumes that IT2FIS has no rules in the beginning, and the learning algorithm adds rules to the network and updates it depending on the prediction error and relative knowledge present in the current sample. As each sample is presented to the network, the meta-cognitive component of the learning algorithm decides what-to-learn, when-to-learn and how-to-learn it, depending on the instantaneous error and spherical potential of the current sample. Whenever a new rule is added or an existing rule is updated, a projection based learning algorithm computes the optimal output weights by minimizing the total error in the network in a computationally efficient manner. The performance of PBL-McIT2FIS is evaluated on a set of benchmark problem and compared to other state-of-the-art algorithms available in literature. The results indicate superior performance of PBL-McIT2FIS.
Starting Page	1510
Ending Page	1516
File Size	723037
Page Count	7
File Format	PDF
ISSN	21614407
e-ISBN	9781479914845
DOI	10.1109/IJCNN.2014.6889610
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Inference algorithms Knowledge engineering Prediction algorithms Fuzzy sets Neural networks Fuzzy logic Measurement uncertainty Projection based learning Interval Type-2 fuzzy systems Meta-cognition Self-regulation
Content Type	Text
Resource Type	Article

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