Algorithms for clustering data
Algorithms for clustering data
Simulated annealing: theory and applications
Simulated annealing: theory and applications
A deterministic annealing approach to clustering
Pattern Recognition Letters
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A simulated annealing algorithm for the clustering problem
Pattern Recognition
Validity Measures for the Fuzzy Cluster Analysis of Orientations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
An evolutionary technique based on K-means algorithm for optimal clustering in RN
Information Sciences—Applications: An International Journal
Resampling Method for Unsupervised Estimation of Cluster Validity
Neural Computation
Robust Full Bayesian Learning for Radial Basis Networks
Neural Computation
Validity-guided (re)clustering with applications to image segmentation
IEEE Transactions on Fuzzy Systems
Application of simulated annealing fuzzy model tuning to umbilical cord acid-base interpretation
IEEE Transactions on Fuzzy Systems
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Fuzzy multi-layer perceptron, inferencing and rule generation
IEEE Transactions on Neural Networks
A cluster validity index for fuzzy clustering
Information Sciences: an International Journal
Data mining with a simulated annealing based fuzzy classification system
Pattern Recognition
Data mining with a simulated annealing based fuzzy classification system
Pattern Recognition
The hybrid genetic fuzzy C-means: a reasoned implementation
FS'06 Proceedings of the 7th WSEAS International Conference on Fuzzy Systems
Joint estimation of source number and DOA using simulated annealing algorithm
Digital Signal Processing
A new multi-objective technique for differential fuzzy clustering
Applied Soft Computing
Analysis of gene microarray data in a soft computing framework
Applied Soft Computing
PMAFC: a new probabilistic memetic algorithm based fuzzy clustering
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Clustering and selecting suppliers based on simulated annealing algorithms
Computers & Mathematics with Applications
A grid-density based technique for finding clusters in satellite image
Pattern Recognition Letters
Improved differential evolution for microarray analysis
International Journal of Data Mining and Bioinformatics
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In this paper, an approach for automatically clustering a data set into a number of fuzzy partitions with a simulated annealing using a Reversible Jump Markov Chain Monte Carlo algorithm is proposed. This is in contrast to the widely used fuzzy clustering scheme, the Fuzzy C-Means (FCM) algorithm, which requires the a priori knowledge of the number of clusters. The said approach performs the clustering by optimizing a cluster validity index, the Xie-Beni index. It makes use of the homogeneous Reversible Jump Markov Chain Monte Carlo (RJMCMC) kernel as the proposal so that the algorithm is able to jump between different dimensions, i.e., number of clusters, until the correct value is obtained. Different moves, like birth, death, split, merge, and update, are used for sampling a candidate state given the current state. The effectiveness of the proposed technique in optimizing the Xie-Beni index and thereby determining the appropriate clustering is demonstrated for both artificial and real-life data sets. In a part of the investigation, the utility of the fuzzy clustering scheme for classifying pixels in an IRS satellite image of Kolkata is studied. A technique for reducing the computation efforts in the case of satellite image data is incorporated.