کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410373 679140 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multiple fuzzy neural networks modeling with sparse data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Multiple fuzzy neural networks modeling with sparse data
چکیده انگلیسی

It is difficult to establish a black-box model for sparse data, because not enough data can be applied for training. This paper presents a novel identification approach using multiple fuzzy neural networks. It focuses on structure and parameters uncertainty which have been widely explored in the literature. Firstly, the sparse data are used within a fixed time interval to generate model structure. Then kernel regression methods are used to generate training data, a stable updating algorithm is proposed to train the membership functions. To cope structure change, a hysteresis strategy is proposed to enable multiple fuzzy neural identifier switching with guaranteed performance. Both theoretic analysis and simulation example show the efficacy of the proposed method.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 73, Issues 13–15, August 2010, Pages 2446–2453
نویسندگان
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