کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4630752 | 1340606 | 2011 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Generalized particle swarm optimization algorithm - Theoretical and empirical analysis with application in fault detection
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
A generalization of the particle swarm optimization (PSO) algorithm is presented in this paper. The novel optimizer, the Generalized PSO (GPSO), is inspired by linear control theory. It enables direct control over the key aspects of particle dynamics during the optimization process. A detailed theoretical and empirical analysis is presented, and parameter-tuning schemes are proposed. GPSO is compared to the classical PSO and genetic algorithm (GA) on a set of benchmark problems. The results clearly demonstrate the effectiveness of the proposed algorithm. Finally, an application of the GPSO algorithm to the fine-tuning of the support vector machines classifier for electrical machines fault detection is presented.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematics and Computation - Volume 217, Issue 24, 15 August 2011, Pages 10175–10186
Journal: Applied Mathematics and Computation - Volume 217, Issue 24, 15 August 2011, Pages 10175–10186
نویسندگان
Željko Kanović, Milan R. Rapaić, Zoran D. Jeličić,