A Self-Evolving Interval Type-2 Fuzzy Neural Network for Nonlinear Systems Identification
نویسندگان
چکیده
منابع مشابه
A Self-Evolving Interval Type-2 Fuzzy Neural Network for Nonlinear Systems Identification
This paper proposes a Self-Evolving Interval Type-2 Fuzzy Neural Network (SEIT2FNN) for nonlinear systems identification. The SEIT2FNN has both on-line structure and parameter learning abilities. The antecedent parts in each fuzzy rule of the SEIT2FNN are interval type-2 fuzzy sets and the fuzzy rules are of the Takagi-Sugeno-Kang (TSK) type. An on-line clustering method is proposed to generate...
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ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 2008
ISSN: 1474-6670
DOI: 10.3182/20080706-5-kr-1001.01283