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- W2393318776 abstract "In order to overcome the Fuzzy C-Means(FCM) clustering algorithm falling into local minimum value and the shortcomings of the initial value of sensitivity,a improved ant colony algorithm based on quantum for fuzzy clustering is proposed.Quantum computing will combine theory and ant colony algorithm to improve the FCM algorithm.It uses quantum genetic algorithm to generate the initial pheromone distribution,and then updates using quantum gates quantum ants carry bits;later uses the ant colony algorithm for global search,parallel computing cluster and other characteristics to avoid falling into local optimal solution.The algorithm is verified to ensure the diversity of population,have a good global convergence and overcome the fuzzy C-means clustering algorithm deficiencies,and can effectively solve the premature convergence problem,so that the final clustering problem quickly and efficiently converges to the global optimal solution." @default.
- W2393318776 created "2016-06-24" @default.
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- W2393318776 date "2011-01-01" @default.
- W2393318776 modified "2023-09-27" @default.
- W2393318776 title "Improved fuzzy C-means clustering algorithm" @default.
- W2393318776 hasPublicationYear "2011" @default.
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