کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1138025 | 1489221 | 2006 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
System reliability forecasting by support vector machines with genetic algorithms
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Support vector machines (SVMs) have been used successfully to deal with nonlinear regression and time series problems. However, SVMs have rarely been applied to forecasting reliability. This investigation elucidates the feasibility of SVMs to forecast reliability. In addition, genetic algorithms (GAs) are applied to select the parameters of an SVM model. Numerical examples taken from the previous literature are used to demonstrate the performance of reliability forecasting. The experimental results reveal that the SVM model with genetic algorithms (SVMG) results in better predictions than the other methods. Hence, the proposed model is a proper alternative for forecasting system reliability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 43, Issues 3–4, February 2006, Pages 262–274
Journal: Mathematical and Computer Modelling - Volume 43, Issues 3–4, February 2006, Pages 262–274
نویسندگان
Ping-Feng Pai,