نتایج جستجو برای: means and fcm
تعداد نتایج: 16851613 فیلتر نتایج به سال:
One of the strategies a company uses to retain its customers is Customer Relationship Management (CRM). CRM manages interactions and supports business build mutually beneficial relationships between companies customers. The utilization information technology, such as data mining used manage data, critical in order be able find out patterns made by when processing transactions. Clustering techni...
The weighting exponent m is called the fuzzifier that can have influence on the clustering performance of fuzzy c-means (FCM) and m∈ [1.5,2.5] is suggested by Pal and Bezdek [13]. In this paper, we will discuss the robust properties of FCM and show that the parameter m will have influence on the robustness of FCM. According to our analysis, we find that a large m value will make FCM more robust...
Fuzzy C-Means (FCM) and hard clustering are the most common tools for data partitioning. However, the presence of noisy observations in the data may cause generation of completely unreliable partitions from these clustering algorithms. Also, application of the Euclidean distance in FCM only produces spherical clusters. In this paper, a new noise-rejection clustering algorithm based on Mahalanob...
Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edg...
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. An interesting extension of FCM is the fuzzy ISODATA (FISODATA) algorithm; it updates cluster number during the algorithm. That's why we can have more or less clusters than the initialization step. It's the power of the fuzzy ISODATA algorithm comparing to FCM. The aim of this paper is...
با توجه به اهمیت و کاربرد سیستم طبقهبندی امتیاز تودهسنگ در مهندسی سنگ، هدف از این مقاله تصحیح کلاسهای نهایی این سیستم طبقهبندی با استفاده از الگوریتمهای خوشهبندی k-means و fuzzy c-means (FCM) است. در سیستم طبقهبندی امتیاز تودهسنگ دادهها توسط یک سری از اطلاعات اولیه بر مبنای نظریات و قضاوتهای تجربی طبقهبندی میشوند ولی با کاربرد الگوریتمهای خوشهبندی در این سیستم طبقهبندی، کلاس...
Fuzzy C-means (FCM) is an unsupervised clustering technique that is often used for the unsuper-vised segmentation of multivariate images. In traditional FCM the clustering is based on spectral information only and the geometrical relationship between neighbouring pixels is not used in the clustering procedure. In this paper, the spatially guided FCM (SG-FCM) algorithm is presented which segment...
-Clustering algorithms are an integral part of both computational intelligence and pattern recognition. It is unsupervised methods for classifying data into subgroups with similarity based inter cluster and intra cluster. In fuzzy clustering algorithms, mainly used algorithm is Fuzzy c-means (FCM) algorithm. This FCM algorithm is efficient only for spherical data when the input of the data stru...
با توجه به اهمیت و کاربرد سیستم طبقه بندی امتیاز توده سنگ در مهندسی سنگ، هدف از این مقاله تصحیح کلاس های نهایی این سیستم طبقه بندی با استفاده از الگوریتم های خوشه بندی k-means و fuzzy c-means (fcm) است. در سیستم طبقه بندی امتیاز توده سنگ داده ها توسط یک سری از اطلاعات اولیه بر مبنای نظریات و قضاوت های تجربی طبقه بندی می شوند ولی با کاربرد الگوریتم های خوشه بندی در این سیستم طبقه بندی، کلاس بندی...
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