کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
381357 | 1437482 | 2010 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hybrid model based on SVM with Gaussian loss function and adaptive Gaussian PSO
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In view of the bad capability of the standard support vector machine (SVM) in field of white noise of input series, a new v-SVM with Gaussian loss function which is call g-SVM is put forward to handle white noises. To seek the unknown parameters of g-SVM, an adaptive normal Gaussian particle swarm optimization (ANPSO) is also proposed. The results of applications show that the hybrid forecasting model based on the g-SVM and ANPSO is feasible and effective, the comparison between the method proposed in this paper and other ones is also given which proves this method is better than v-SVM and other traditional methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 23, Issue 4, June 2010, Pages 487–494
Journal: Engineering Applications of Artificial Intelligence - Volume 23, Issue 4, June 2010, Pages 487–494
نویسندگان
Qi Wu, Shuyan Wu, Jing Liu,