Palaniswami, "Fuzzy c-means algorithms for very large data," IEEE Trans. Fuzzy Syst., vol. 20, pp. 1130-1146, Dec. 2012.T. C. Havens, J. C. Bezdek, C. Leckie, L. O. Hall, and M. Palaniswami, "Fuzzy c-means algorithms for very large data," Fuzzy Systems, IEEE Transactions ...
We present a hotspot detection method based on the Extended Fuzzy C-Means (EFCM) algorithm for large (L) and very large (VL) datasets of events. Extensions of four VL-FCM algorithms are presented. We test our method applying these algorithms to an L dataset composed from the epicenters of...
Parallel Fuzzy c-Means Clustering for Large Data Sets Terence Kwok1, Kate Smith1, Sebastian Lozano2, and David Taniar1 1 School of Business Systems, Faculty of Information Technology, Monash University, Australia {terence.kwok, kate.smith, david.taniar}@infotech.monash.edu.au 2 Escuela Superior...
Comparison of K-Means and Fuzzy C-Means Data Mining Algorithms for Analysis of Management Information: An Open Source CaseFuzzy C-MEANS algorithmK-MEANSData Miningmanagement data analysisThis research presents the knowledge discovery using Data Mining from the organization and with a KPI management ...
However, it is difficult for the fuzzy c-means algorithm to satisfy the real-time requirements of IoT big data clustering because each object has a large number of attributes. Specially, a large number of attributes will significantly increase the computational cost of the fuzzy c-means algorithm...
very sensitive to the choice of the additional parameters needed by the PCM model. Timm et al. [13]–[15] proposed two possibilistic fuzzy clus- tering algorithms that can avoid the coincident cluster problem of PCM. In [13] and [14], the authors modified the PCM ob- ...
James CB. Pattern recognition with fuzzy objective function algorithms. Berlin: Springer; 2013. Google Scholar Hung YW, Chiu YH, Jou YC, Chen WH, Cheng KS. Bed posture classification based on artificial neural network using fuzzy c-means and latent semantic analysis. J Chin Inst Eng. 2015;...
Interpretability is the dominant feature of a fuzzy model in security-oriented fields. Traditionally fuzzy models based on expert knowledge have obtained well interpretation innately but imprecisely. Numerical data based fuzzy models perform well in prec
2.2. Single-Pass Fuzzy c Means and Online Fuzzy c Means The spFCM and oFCM are two incremental fuzzy clustering algorithms designed based on FCM for large data. These two algorithms employ wFCM to consider the relative importance of centroids and objects. The process of spFCM is shown as ...
To do so, a set of benchmarking data sets of varying sizes and complexities are taken and run through implementations of the algorithms, and the performance indices are calculated and recorded for later analysis. The algorithms explored in this work are K-Means and Fuzzy C-Means as well as ...