کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
395334 665953 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of different strategies of utilizing fuzzy clustering in structure identification
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Comparison of different strategies of utilizing fuzzy clustering in structure identification
چکیده انگلیسی

Fuzzy systems approximate highly nonlinear systems by means of fuzzy “if–then” rules. In the literature, various algorithms are proposed for mining. These algorithms commonly utilize fuzzy clustering in structure identification. Basically, there are three different approaches in which one can utilize fuzzy clustering; the first one is based on input space clustering, the second one considers clustering realized in the output space, while the third one is concerned with clustering realized in the combined input–output space. In this study, we analyze these three approaches. We discuss each of the algorithms in great detail and offer a thorough comparative analysis. Finally, we compare the performances of these algorithms in a medical diagnosis classification problem, namely Aachen Aphasia Test. The experiment and the results provide a valuable insight about the merits and the shortcomings of these three clustering approaches.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 177, Issue 23, 1 December 2007, Pages 5153–5162
نویسندگان
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