Intuitionistic fuzzy c-means clustering algorithm based on a novel weighted proximity measure and genetic algorithm

In the era of big data, the research on clustering technologies is a popular topic because they can discover the structure of complex data sets with minimal prior knowledge. Among the existing soft clustering technologies, as an extension of fuzzy c-means (FCM) algorithm, the intuitionistic FCM (IFC...

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Vydáno v:	International journal of machine learning and cybernetics Ročník 12; číslo 3; s. 859 - 875
Hlavní autoři:	Hou, Wen-hui, Wang, Yi-ting, Wang, Jian-qiang, Cheng, Peng-Fei, Li, Lin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2021 Springer Nature B.V
Témata:	Accuracy Artificial Intelligence Big Data Cluster analysis Clustering Complex Systems Computational Intelligence Control Datasets Engineering Fuzzy sets Genetic algorithms Heuristic Mechatronics Optimization algorithms Original Article Outliers (statistics) Parameter identification Pattern Recognition Proximity Robotics Similarity measures Systems Biology Correlation coefficient Genetic algorithm (GA) Intuitionistic fuzzy c-means (IFCM) algorithm Similarity measure Intuitionistic fuzzification
ISSN:	1868-8071, 1868-808X
On-line přístup:	Získat plný text
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