کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4947724 | 1439591 | 2017 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel automatic fuzzy clustering algorithm based on soft partition and membership information
ترجمه فارسی عنوان
یک الگوریتم خوشه بندی اتوماتیک فازی اتوماتیک بر اساس پارتیشن نرم افزاری و اطلاعات عضویت
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In the field of data clustering, finding the cluster numbers automatically and generating reliable clusters for a given dataset are fundamental but challenging tasks. Recently, a clustering analysis algorithm for the automatic identification of cluster numbers was presented, and it achieves accurate clustering results for those datasets with complex structures. Unfortunately, this algorithm utilizes a hard partition approach in the process of integration and does not make full use of the membership information from each fuzzy c-means (FCM) clustering result. Thus, this scheme has to integrate many more FCM clustering results and also requires many iterations during the process of iterative graph partitioning. To address this problem, an automatic fuzzy clustering algorithm is proposed in this paper, combining the soft partition method with the membership information from each FCM clustering result. Finally, extensive experiments are performed, and under the premise of obtaining accurate clustering results simultaneously, the proposed algorithm can effectively decrease the number of FCM clustering results in the process of integration compared with the original algorithm. Furthermore, the number of iterations of the proposed scheme in the iterative graph partitioning process is half that of the original approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 236, 2 May 2017, Pages 104-112
Journal: Neurocomputing - Volume 236, 2 May 2017, Pages 104-112
نویسندگان
Chen Hai-peng, Shen Xuan-Jing, Lv Ying-da, Long Jian-Wu,