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Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 27-745
Full Name: Long Yu
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: School of Electrical Engineering,Southwest Jiaotong University,Chengdu
Country: CHINA
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E-mail address: yulong.swjtu@163.com
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Title of the Paper: reduced-set vector-based interval type-2 fuzzy neural network
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Number of paper pages: 10
Abstract: This paper describes an interval type-2 fuzzy modeling framework, reduced-set vector-based interval type-2 fuzzy neural network (RV-based IT2FNN), to characterize the representation in fuzzy logic inference procedure. The model proposed introduces the concept of interval kernel to interval type-2 fuzzy membership, and provides an architecure to extract reduced-set vectors for generating interval type-2 fuzzy rules. Thus, the overall RV-based IT2FNN can be represented as series expansion of interval kernel, and it does not have to determine the number of rules in advance. By using a hybrid learning mechanism, the proposed RV-based IT2FNN can construct an input-ouput mapping from the training data in the form of fuzzy rules. At last, simulation results show that the RV-based IT2FNN obtained possesses nice generalization and transparency.
Keywords: Interval type-2; Fuzzy modeling; Reduced-set; Interval kernel; Insensitive learning
EXTENSION of the file: .pdf
Special (Invited) Session: reduced-set vector learning based on hybrid kernels for interval type 2 fuzzy modeling
Organizer of the Session: 616-103
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