Cultural Emperor Penguin Optimizer and Its Application for Face Recognition

Table 2

Parameter setting of nine algorithms.

Algorithms	Parameters	Values
Cultural emperor penguin optimizer (CEPO)	Size of population	80
	Control parameter	[1.5, 2]
	Control parameter	[2, 3]
	Movement parameter	2
	The constant	0.06
	Maximum iteration	100
Moth-flame optimization (MFO) [9]	Size of population	80
	Convergence constant	[−1, −2]
	Logarithmic spiral	0.75
	Maximum iteration	100
Grey wolf optimizer (GWO) [8]	Size of population	80
	Control parameter	[0, 2]
	Maximum iteration	100
Particle swarm optimization (PSO) [6]	Size of population	80
	Inertia weight	0.75
	Cognitive and social coeff	1.8, 2
	Maximum iteration	100
Genetic algorithm (GA) [5]	Size of population	80
	Probability of crossover	0.9
	Probability of mutation	0.05
	Maximum iteration	100
Cultural algorithm (CA) [14]	Size of population	80
	The constant	0.06
	Maximum iteration	100
Emperor penguin optimizer (EPO) [12]	Size of population	80
	Control parameter	[1.5, 2]
	Control parameter	[2, 3]
	Movement parameter	2
	Maximum iteration	100
Cultural firework algorithm (CFA) [17]	Size of population	80
	Cost parameter	0.025, 0.2
	The constant	0.3
	Maximum iteration	100
Emperor penguin and social engineering optimizer (EPSEO) [13]	Size of population	80
	Rate of training	0.2
	Rate of spotting an attack	0.05
	Number of attacks	50
	Control parameter	[1.5, 2]
	Control parameter	[2, 3]
	Movement parameter	2
	Maximum iteration	100