In medical applications all effectual agents in patient health must be fast, even medical algorithms such as clustering ones. In this paper an optimized technique is presented to decrease execution time and iterations of standard Fuzzy C-Means (FCM) alghorythm. New approach calculates cluster center in each iteration by new formula. Applying proposed method decreases the complexity of FCM algor...

This paper presents a new proposed technique to identify the coherent groups of generators using fuzzy c-means clustering algorithm (FCM). The proposed technique is based on a proposed coherency criterion introduced by using time response of the linearized power system model that reveal the relations between generators which is the integral of the square of the rotor angle difference (ISEδ) whi...

Image segmentation is the foremost process in medical image processing. It aids the diagnostic and clinical analysis of MRI (Magnetic Resonance Imaging) images that were acquired through the most complex procedures of medical diagnostics. The earliest soft computing techniques in segmenting images were carried out through Fuzzy C-Means (FCM) and similar extensions of various clustering algorith...

Classical fuzzy C -means (FCM) clustering is performed in the input space, given the desired number of clusters. Although it has proven effective for spherical data, it fails when the data structure of input patterns is non-spherical and complex. In this paper, we present a novel kernel-based fuzzy C-means clustering algorithm (KFCM). Its basic idea is to transform implicitly the input data int...

We compared the previous study about clustering welfare of Indonesian people using Fuzzy C-Means (FCM) approach to a recent study, Gaussian mixture model (GMM). Both which were soft clustering. The case analyzes by classifying 34 provincial data in Indonesia, based on eight indicator variables 2017, Central Statistics Agency had issued. FCM and GMM approaches determine better level accuracy Sil...

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The traditional fuzzy C-means(FCM) algorithm is an optimization algorithm based on gradient descending, it is sensitive to the initial condition and liable to be trapped in a local optimum. Search space smoothing allows a local search heuristics to escape from a poor, local optimum. In this paper, an improved FCM algorithm based on search space smoothing is proposed. By designing a proper smoot...

Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is ...