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- W2808033023 abstract "The initial clustering center of the traditional K-means algorithm is randomly generated from the data set which leads it easily gets the local optimal solution rather than the global optimal solution. In this paper, a high-dimensional quantum genetic clustering method is proposed in which each quantum bit is decomposed into a plurality of parallel genes according to a high-dimensional quantum encoding scheme and it effectively expands the search space and enhances the efficiency of parallel search. A quantum updating strategy comes out by combining the high-dimensional coding scheme and the dynamically adjustment rotation angle mechanism to renew the individual. Quantum mutation is implemented by quantum non-gate mutation strategy to enhance the global searching ability of the algorithm. Experiments show that the algorithm is not only better in clustering accuracy, but also faster in convergence." @default.
- W2808033023 created "2018-06-21" @default.
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- W2808033023 date "2018-03-01" @default.
- W2808033023 modified "2023-09-24" @default.
- W2808033023 title "Quantum genetics clustering algorithm based on high-Dimensional and multi-chain coding scheme" @default.
- W2808033023 doi "https://doi.org/10.1109/icaci.2018.8377478" @default.
- W2808033023 hasPublicationYear "2018" @default.
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