کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
409679 | 679083 | 2013 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Differentiating adaptive Neuro-Fuzzy Inference System for accurate function derivative approximation
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
Function and its partial derivative approximation based upon a set of discrete dataset are important issues in soft computing. Several function approximators have been presented most of them fits a model to the dataset so that the Mean Squared Error is minimized. In this paper, we propose to calculate the derivative of the Neuro-Fuzzy function approximator directly according to the parametric structure of the system and the available dataset. A criterion for derivative approximation is defined based on a combination of MSE and Approximate Entropy. According to this criterion, the superiority of the Neuro-Fuzzy model is demonstrated in comparison with some other types of Artificial Neural Networks and Polynomial models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 103, 1 March 2013, Pages 232–238
Journal: Neurocomputing - Volume 103, 1 March 2013, Pages 232–238
نویسندگان
Omid Khayat, Hadi Chahkandi Nejad, Fereidoon Nowshiravan Rahatabad, Mahdi Mohammad Abadi,