کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385731 | 660872 | 2011 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hybrid fuzzy support vector classifier machine and modified genetic algorithm for automatic car assembly fault diagnosis
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper presents a new version of fuzzy support vector machine to diagnose automatic car assembly fault diagnosis, the input and output variables are described as fuzzy numbers and the metric on fuzzy number space is defined. Then by combining the fuzzy theory with v-support vector machine, the fuzzy v-support vector classifier machine (Fv-SVCM) is proposed. A fault diagnosis method based on Fv-SVCM and its relevant parameter-choosing algorithm is put forward. The results of the application in car assembly diagnosis confirm the feasibility and the validity of the diagnosis method. Compared with the fuzzy neural network (FNN) model, Fv-SVCM method requires fewer samples and has better estimating precision.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 3, March 2011, Pages 1457–1463
Journal: Expert Systems with Applications - Volume 38, Issue 3, March 2011, Pages 1457–1463
نویسندگان
Qi Wu,