Summary of FCM algorithm literature

In recent years, FCM algorithm has become more and more popular, and has been applied to various fields, and the improvement of FCM algorithm is more and more. This paper summarizes the recent two years of algorithm improvement, if there are improved algorithms not all please find out for yourself oh, too many papers. As the reference documents are English papers, here is not translated, after all, I am not crooked nuts.

2014

1. D-ficca (density-based Fuzzy imperialist competitive clustering algorithm)
   References: d-ficca:a density-based fuzzy imperialist competitive clustering algorithm for intrusion detection in wireless senso R networks.

2. Fggca
   References: Fuzzy granular gravitational clustering algorithm for multivariate data

2013

1. Type-2 FCM
   References: A modified interval type-2 fuzzy C-means algorithm with application in MR image segmentation

2. grfkm
   References: Rough clustering using generalized fuzzy clustering algorithm

3. F-tclust
   References: Robust constrained fuzzy clustering

4. Vague C-means
   References: Vague C-means Clustering algorithm

2012

1. Grfcm
   References: Generalized rough fuzzy c-means algorithm for brain MR image segmentation

2. Ssfca
   References: A semi-supervised fuzzy Clustering algorithm applied to gene expression data

2011

1. Possiblistic FCM
   References: A modified possibilistic fuzzy C-means Clustering algorithm for bias field estimation and segmentation of brain MR IM Age

2. Recursive FCM
   References: Recursive fuzzy C-means clustering for Recursive fuzzy identification of time-varying processes

2010

1. Mfcm
   References: semi-supervised outlier detection based on fuzzy rough
   C-means Clustering

2. Frssod
   References: Median fuzzy C-means for clustering dissimilarity data

Summary of FCM algorithm literature