In this paper, we propose new fuzzy c-means method for improving the magnetic resonance imaging (MRI) segmentation. The proposed method called “possiblistic fuzzy c-means (PFCM)” which hybrids the fuzzy c-means (FCM) and possiblistic c-means (PCM) functions. It is realized by modifying the objective function of the conventional PCM algorithm with Gaussian exponent weights to produce memberships...

In order to reduce the time for customers select commodities they are interested in, improve purchase efficiency, success rate of sales merchants, and create greater economic benefits enterprises this project collects information data e-commerce users, using neural network model analyze mine characteristics shopping records users. According analysis results, a user commodity recommendation syst...

--Thresholding, the problem of pixel classification is attempted here using fuzzy clustering algorithms. The segmented regions are fuzzy subsets, with soft partitions characterizing the region boundaries. The validity of the assumptions and thresholding schemes are investigated in the presence of distinct region proportions. The hard k means and fuzzy c means algorithms have been found useful w...