کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7001297 1454778 2018 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting running-in wear volume with a SVMR-based model under a small amount of training samples
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی شیمی کلوئیدی و سطحی
پیش نمایش صفحه اول مقاله
Predicting running-in wear volume with a SVMR-based model under a small amount of training samples
چکیده انگلیسی
This paper proposes a support vector machine regression (SVMR) model to predict running-in wear volume, with field surface topography parameters and working conditions as the input variables, under the condition that the amount of training samples is very limited. Experimental results proved the effectiveness of the SVMR-based model with a small amount of training samples. Based on the established prediction model, the impacts of the field surface parameters on running-in wear volume have been analyzed. The results show that Sku has the largest influence on running-in wear volume, Sdq the second, and Svk the least.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tribology International - Volume 128, December 2018, Pages 349-355
نویسندگان
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