Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Mining time-changing data streams
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Evolving rule-based models: a tool for design of flexible adaptive systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Fuzzy Modeling for Control
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Essentials of Fuzzy Modeling and Control
Essentials of Fuzzy Modeling and Control
Dynamic data assigning assessment clustering of streaming data
Applied Soft Computing
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
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A simplified clustering algorithm that enables on-line partitioning of data streams is proposed. The algorithm applies adaptive-distance metric to identify clusters with different shape and orientation. It is applicable to a wide range of practical evolving system type applications as diagnostics and prognostics, system identification, real time classification, and process quality monitoring and control.