کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
806246 | 905281 | 2007 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A support vector machine integrated system for the classification of operation anomalies in nuclear components and systems
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی مکانیک
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
A support vector machine (SVM) approach to the classification of transients in nuclear power plants is presented. SVM is a machine-learning algorithm that has been successfully used in pattern recognition for cluster analysis. In the present work, single- and multiclass SVM are combined into a hierarchical structure for distinguishing among transients in nuclear systems on the basis of measured data. An example of application of the approach is presented with respect to the classification of anomalies and malfunctions occurring in the feedwater system of a boiling water reactor. The data used in the example are provided by the HAMBO simulator of the Halden Reactor Project.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 92, Issue 5, May 2007, Pages 593–600
Journal: Reliability Engineering & System Safety - Volume 92, Issue 5, May 2007, Pages 593–600
نویسندگان
Claudio M. Rocco S., Enrico Zio,