کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6858265 665693 2014 24 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Interval Type-2 Relative Entropy Fuzzy C-Means clustering
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Interval Type-2 Relative Entropy Fuzzy C-Means clustering
چکیده انگلیسی
Fuzzy set theory especially Type-2 fuzzy set theory provides an efficient tool for handling uncertainties and vagueness in real world observations. Among various clustering techniques, Type-2 fuzzy clustering methods are the most effective methods in the case of having no prior knowledge about observations. While uncertainties in Type-2 fuzzy clustering parameters are investigated by researchers, uncertainties associated with membership degrees are not very well discussed in the literature. In this paper, investigating the latter uncertainties is our concern and Interval Type-2 Relative Entropy Fuzzy C-Means (IT2 REFCM) clustering method is proposed. The computational complexity of the proposed method is discussed and its performance is examined using several experiments. The obtained results show that the proposed method has a very good ability in detecting noises and assignment of suitable membership degrees to observations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 272, 10 July 2014, Pages 49-72
نویسندگان
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