Abstract
This paper introduces a new improved algorithm called chaotic PSO (CPSO) based on the thought of chaos optimization to solve multiple sequence alignment. For one thing, the chaotic variables are generated between 0 and 1 when initializing the population so that the particles are distributed uniformly in the solution space. For another thing, the chaotic sequences are generated using the Logistic mapping function in order to make chaotic search and strengthen the diversity of the population. The simulation results of several benchmark data sets of BAliBase show that the improved algorithm is effective and has good performances for the data sets with different similarity.
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Lei, Xj., Sun, Jj., Ma, Qz. (2009). Multiple Sequence Alignment Based on Chaotic PSO. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2009. Communications in Computer and Information Science, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04962-0_40
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DOI: https://doi.org/10.1007/978-3-642-04962-0_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04961-3
Online ISBN: 978-3-642-04962-0
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