کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4974440 | 1365533 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel APSO-aided weighted LSSVM method for nonlinear hammerstein system identification
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Identification of Hammerstein nonlinear models has received much attention due to its ability to describe a wide variety of nonlinear systems. A novel identification approach based on intelligent optimal weighted least squares SVM (WLSSVM) is proposed for Hammerstein system, where a new adaptive particle swarm optimization algorithm (APSO) using the evolutionary state estimation technique and mutation operator is applied. The proposed method not only has fast convergence to the global optimal solution but also has good identification results. The comparison researches are carried out among the proposed method, WLSSVM, LSSVM and RIV methods in detail. The research results show the effectiveness of proposed APSO-WLSSVM method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Franklin Institute - Volume 354, Issue 4, March 2017, Pages 1892-1906
Journal: Journal of the Franklin Institute - Volume 354, Issue 4, March 2017, Pages 1892-1906
نویسندگان
Liang Ma, Xinggao Liu,