Bodyanskiy, Ye. V.Shafronenko, A. Yu.2020-11-132020-11-132019Ye. Bodyanskiy, A. Shafronenko Online algorithm for Рossibilitic fuzzy clustering based on evolutionary cat swarm op-timization. Science and Education a New Dimension. Natural and Tech-nical Sciences - VII(23), Issue: 193, 2019 - P. 86-88http://openarchive.nure.ua/handle/document/13787The problem of clustering of multidimensional observations is often found in many applications related to data mining and exploratory data analysis. The traditional approach to solving these problems requires that every observation could belong to only one cluster at a more natural is situations when a feature vector with the various possible levels of memberships can belong to multiple classes. This situation is the subject of fuzzy cluster analysis, rapidly developing now. We propose online adaptive approach for this task solving.enFuzzy clusteringlearning rulecat swarm optimizationtracing modeseeking modeArticle