کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9740169 | 1489228 | 2005 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A self-constructing compensatory neural fuzzy system and its applications
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
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چکیده انگلیسی
A self-constructing compensatory neural fuzzy system (SCCNFS) for nonlinear system identification and control is proposed in this paper. The compensatory fuzzy reasoning method uses adaptive fuzzy operations of a neural fuzzy network to make the fuzzy logic system more adaptive and effective. An online learning algorithm is proposed to automatically construct the SCCNFS. The fuzzy rules are created and adapted as online learning proceeds through simultaneous structure and parameter learning. The structure learning is based on the fuzzy similarity measure and the parameter learning is based on the backpropagation algorithm. The advantages of the proposed learning algorithm are that it converges quickly and that the fuzzy rules that are obtained are more precise. The performance of SCCNFS compares excellently with other various existing models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 42, Issues 3â4, August 2005, Pages 339-351
Journal: Mathematical and Computer Modelling - Volume 42, Issues 3â4, August 2005, Pages 339-351
نویسندگان
Cheng-Jian Lin, Cheng-Hung Chen,