Refinement of K-Means and Fuzzy C-Means

Comparative Analysis of K-Means and Fuzzy C-Means Algorithms

In the arena of software, data mining technology has been considered as useful means for identifying patterns and trends of large volume of data. This approach is basically used to extract the unknown pattern from the large set of data for business as well as real time applications. It is a computational intelligence discipline which has emerged as a valuable tool for data analysis, new knowled...

تصحیح سیستم طبقه‌بندی امتیاز توده‌سنگ با استفاده ‌از الگوریتم‌های‌ خوشه‌بندی ‌‌k-means و ‌fuzzy c-means

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...

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Bilateral Weighted Fuzzy C-Means Clustering

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

Evaluation of k-Means and fuzzy C-means segmentation on MR images of brain

Glioblastoma multiforme; Necrotic focus; Vasogenic edema; Bilateral filter; Contrast limited adaptive histogram equilization Abstract This paper does the qualitative comparison of Fuzzy C-means (FCM) and k-Means segmentation, with histogram guided initialization, on tumor edema complex MR images. The accuracy of any segmentation scheme depends on its ability to distinguish different tissue clas...