Abstract
Using DNA computation to solve clustering problem is a new approach in this field. In the process of problem solving, we use DNA strands to assign vertices and edges, constructing the shortest Hamilton path and cutting branches whose length is longer than the threshold we gave getting the initial clustering result. For improving the quality, we do the iterative calculation, getting clusters for every produced cluster, we deal all of the process with DNA computation in test tubes, reducing the time complexity obviously by DNAs high parallelism. In this paper, we give the process and analysis of our algorithm, illustrating the feasibility of the method.
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Kang, Z., Liu, X., Xue, J. (2014). DNA Computation Based Clustering Algorithm. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8794. Springer, Cham. https://doi.org/10.1007/978-3-319-11857-4_53
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DOI: https://doi.org/10.1007/978-3-319-11857-4_53
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11856-7
Online ISBN: 978-3-319-11857-4
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