JOURNAL ARTICLE

A Knowledge Context Fuzzy Clustering Method Based on Genetic Algorithm

Faping ZhangLi LiCuixiang Zhou

Year: 2017 Journal:   MATEC Web of Conferences Vol: 139 Pages: 00064-00064   Publisher: EDP Sciences

Abstract

\nA fuzzy clustering method based on genetic algorithm is proposed aiming at the problem of automatic clustering of knowledge context. Firstly, the knowledge context model is constructed to determine the similarity measure of knowledge context. Then the initial clustering centers are obtained based on the density peak method. Then the fuzzy C mean clustering result is solved by genetic algorithm, and the clustering of knowledge context is realized. Finally, the knowledge context clustering of an aircraft part design process is taken as an example to illustrate the effectiveness of the algorithm.\n

Keywords:
Cluster analysis Fuzzy clustering Correlation clustering Data mining CURE data clustering algorithm FLAME clustering Context (archaeology) Computer science Canopy clustering algorithm Artificial intelligence Genetic algorithm Fuzzy logic Data stream clustering Similarity (geometry) Pattern recognition (psychology) Machine learning Algorithm Mathematics

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Topics

Advanced Clustering Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Anomaly Detection Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Industrial Technology and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering

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