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Table 1 The experimental results on the first data set.

From: A novel approach to phylogenetic tree construction using stochastic optimization and clustering

Dataset GA AAPTC
  mean S.D. high low mean S.D. high low
S11 8.78 0.06 9.81 7. 40 9.83 0.02 9.94 9.77
    (68345) (42157)    (65487) (382914)
S12 5.39 0.35 9.75 5.11 9.67 0.04 9. 81 9.62
    (59623) (34728)    (57631) (26738)
S13 9.64 0.11 9.83 8.92 9.88 0.06 9.96 9.85
    (72100) (32572)    (76895) (15201)
S14 5.78 0.42 9.69 5.03 9.86 0.07 9.91 9.70
    (69805) (25437)    (82965) (43346)
  1. Table 1 gives the results on the first set of simulated data. The optimal tree topology of these data is known in advance because they are generated for a predefined tree topology, and the fitness value of the optimal solution is just 10. Form experimental results given in table 1, both methods could find the optimal tree topology. In the cases of S11, S12, S13 and S14, AAPTC finds the optimal topology for all trials, whereas the GA method falls into local convergence eight times with average fitness value of 5.39 and six times with average fitness value of 5.78 on S12 and S14 respectively. Therefore, ACTP can get more global and higher fitness valued phylogenetic trees than GA.