RBF Networks Exploiting Supervised Data in the Adaptation of Hidden Neuron Parameters
AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Influential Rule Search Scheme (IRSS)-A New Fuzzy Pattern Classifier
IEEE Transactions on Knowledge and Data Engineering
A cluster validity index for fuzzy clustering
Pattern Recognition Letters
A Global Optimization RLT-based Approach for Solving the Fuzzy Clustering Problem
Journal of Global Optimization
Vector quantization and fuzzy ranks for image reconstruction
Image and Vision Computing
Engineering Applications of Artificial Intelligence
Output value-based initialization for radial basis function neural networks
Neural Processing Letters
Image segmentation by clustering of spatial patterns
Pattern Recognition Letters
Filtering of interferometric SAR phase images as a fuzzy matching-pursuit blind estimation
EURASIP Journal on Applied Signal Processing
A convergence theorem for the fuzzy subspace clustering (FSC) algorithm
Pattern Recognition
Problems and solutions for anchoring in multi-robot applications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Marco Somalvico Memorial Issue
Anomaly detection in mobile communication networks using the self-organizing map
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - VIII Brazilian Symposium on Neural Networks
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Gravitational Fuzzy Clustering
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
A case study of applying data mining techniques in an outfitter's customer value analysis
Expert Systems with Applications: An International Journal
An efficient approach for building customer profiles from business data
Expert Systems with Applications: An International Journal
Clustering: A neural network approach
Neural Networks
Scalable Clustering for Mining Local-Correlated Clusters in High Dimensions and Large Datasets
Fundamenta Informaticae - Intelligent Data Analysis in Granular Computing
Use of a fuzzy granulation--degranulation criterion for assessing cluster validity
Fuzzy Sets and Systems
A fuzzy minimax clustering model and its applications
Information Sciences: an International Journal
An immune network for contextual text data clustering
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Fuzzy concepts in vector quantization training
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
Near-Optimal fuzzy systems using polar clustering: application to control of vision-based arm-robot
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Engineering Applications of Artificial Intelligence
Soft clustering -- Fuzzy and rough approaches and their extensions and derivatives
International Journal of Approximate Reasoning
Enhanced interval type-2 fuzzy c-means algorithm with improved initial center
Pattern Recognition Letters
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For pt.I see ibid., p.775-85. In part I an equivalence between the concepts of fuzzy clustering and soft competitive learning in clustering algorithms is proposed on the basis of the existing literature. Moreover, a set of functional attributes is selected for use as dictionary entries in the comparison of clustering algorithms. In this paper, five clustering algorithms taken from the literature are reviewed, assessed and compared on the basis of the selected properties of interest. These clustering models are (1) self-organizing map (SOM); (2) fuzzy learning vector quantization (FLVQ); (3) fuzzy adaptive resonance theory (fuzzy ART); (4) growing neural gas (GNG); (5) fully self-organizing simplified adaptive resonance theory (FOSART). Although our theoretical comparison is fairly simple, it yields observations that may appear parodoxical. First, only FLVQ, fuzzy ART, and FOSART exploit concepts derived from fuzzy set theory (e.g., relative and/or absolute fuzzy membership functions). Secondly, only SOM, FLVQ, GNG, and FOSART employ soft competitive learning mechanisms, which are affected by asymptotic misbehaviors in the case of FLVQ, i.e., only SOM, GNG, and FOSART are considered effective fuzzy clustering algorithms