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Fuzzy Bayesian Classifier for LR-Type Fuzzy Numbers

عنوان مقاله: Fuzzy Bayesian Classifier for LR-Type Fuzzy Numbers
شناسه ملی مقاله: FJCFIS02_070
منتشر شده در دومین کنگره مشترک سیستمهای فازی و هوشمند ایران در سال 1387
مشخصات نویسندگان مقاله:

Hadi Sadoghi Yazdi - Engineering Department, Tarbiat Moallem University of Sabzevar
Mehri Sadoghi Yazdi - Shahid Beheshti University of Tehran

خلاصه مقاله:
Bayesian decision theory is a fundamental statistical approach to the problem of pattern classification. In this paper, we proposed a fuzzyBayesian classifier (FBC) over LR-type fuzzy numberswith unknown conditional probability density function. A new version of K-NN method is used to estimateconditional probability density function for Bayesian classification of fuzzy numbers. Experimentations show that this method has good recognition rate over fuzzy numbers even in presence of noise

کلمات کلیدی:
Bayesian decision theory, pattern classification, fuzzy Bayesian classifier, LR-type fuzzy number, K-NN method

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/203781/