Comparison of convergence speed between DMBBPSO, FisBBPSO, PBBPSO, TBBPSO and ETBBPSO, f24.

(a) iteration 0–6000, (b) iteration 6000–10000 the unit is 100 iterations.

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Bibliographic Details
Main Author:	Yule Sun (16015342) (author)
Other Authors:	Jia Guo (156736) (author), Ke Yan (331581) (author), Yi Di (4445635) (author), Chao Pan (132139) (author), Binghu Shi (16015345) (author), Yuji Sato (81706) (author)
Published:	2023
Subjects:	Molecular Biology Space Science Biological Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified personal best position large global search experimental results demonstrate conducting global searches cec2017 benchmark functions avoid premature convergence art evolutionary algorithms precision local search deep memory bare objective optimization problems layer activation strategy every single particle maintaining high accuracy particle swarm optimization ability objective optimizers local optima deep memories xlink "> turn enhances reliable solution rapidly lose perform high las enhances las enables las ). important challenge five state evaluation process control group
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Comparison of convergence speed between DMBBPSO, FisBBPSO, PBBPSO, TBBPSO and ETBBPSO, <i>f</i><sub>24</sub>.