Fig 1.
Flowchart for the proposed MOPSOSA algorithm.
Fig 2.
Flowchart for initializing particle swarm.
Fig 3.
Flowchart for the MOSA technique applied in MOPSOSA.
Table 1.
Description of the artificial and real-life datasets.
Fig 4.
Graphs of the artificial datasets.
(a) Sph_5_2. (b) Sph_4_3. (c) Sph_6_2. (d) Sph_10_2. (e) Sph_9_2. (f) Pat1. (g) Pat2. (h) Long1. (i) Sizes5. (j) Spiral. (k) Square1. (l) Square4. (m) Twenty. (n) Fourty.
Table 2.
Parameter settings used in MOPSOSA algorithm.
Table 3.
F-measure value and the number of clusters for different datasets obtained by MOPSOSA compared with those acquired by GenClustMOO, GenClustPESA2, MOCK, and VGAPS algorithms.
Table 4.
Averages and standard deviations for the F-measure values on the different datasets obtained from MOPSOSA, GenClustMOO, GenClustPESA2, MOCK, VGAPS, KM, and SL algorithms.
Fig 5.
Graphs of the artificial datasets after applying the MOPSOSA algorithm.
(a) Sph_5_2. (b) Sph_4_3. (c) Sph_6_2. (d) Sph_10_2. (e) Sph_9_2. (f) Pat1. (g) Pat2. (h) Long1. (i) Sizes5. (j) Spiral. (k) Square1. (l) Square4. (m) Twenty. (n) Fourty.