Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely used to understand consumer behaviour. In this study, we propose a strategy of analysis, by combining the Bagged Clustering (B...

Despite its potential advantages for fMRI analysis, fuzzy C-means (FCM) clustering suffers from limitations such as the need for a priori knowledge of the number of clusters, and unknown statistical significance and instability of the results. We propose a randomization-based method to control the false-positive rate and estimate statistical significance of the FCM results. Using this novel app...

This study aims to empirically analyze teaching-learning-based optimization (TLBO) and machine learning algorithms using k-means fuzzy c-means (FCM) for their individual performance evaluation in terms of clustering classification. In the first phase, (k-means FCM) were employed independently accuracy was evaluated different computational measures. During second non-clustered data obtained from...

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...

For the design and planning of gas-fired boiler system, load is an important basic data. Load clustering analysis, combined with application data mining technology gas excavates hidden patterns in a large number disordered irregular loads, classifies them, so as to solve many problems system. The current methods have more or less problems. invention first carries out PVA dimension reduction pro...

This study proposes a new single-solution based metaheuristic, namely the Vortex Search algorithm (VS), for fuzzy clustering of ECG beats. The newly proposed metaheuristic is quite simple and highly competitive when compared to the population-based metaheuristics. In order to study the performance of the proposed method a number of experiments are performed over a dataset which is created by us...

Image segmentation plays a major role in medical imaging applications. During last decades, developing robust and efficient algorithms for medical image segmentation has been a demanding area of growing research interest. The renowned unsupervised clustering method, Fuzzy C-Means (FCM) algorithm is extensively used in medical image segmentation. Despite its pervasive use, conventional FCM is hi...

FCM is one of a conventional clustering method and has been generally applied for medical image segmentation. On the other hand, conventional FCM at all times suffers from noise in the images. Even though the unique FCM algorithm yields good results for segmenting noise free images, it fails to segment images corrupted by noise, outliers and other imaging artifact. The most important shortcomin...