A Danger-Theory-Based Immune Network Optimization Algorithm

Table 3

Results (errors) in 2-dimensional spaces.

		Function errors of the optimal solution	Number of peaks
	dt-aiNet	1.62∗10^−11 (2.1∗10^−11)	1 (0)
𝐹2	CLONALG	5.78∗10^1 (3.34∗10^1)	1 (1.46)
	opt-aiNet	6.01∗10^−5 (4.61∗10^−5)	5 (1.42)
	Dopt-aiNet	2.13∗10^−1 (4.5∗10^−1)	2.41 (1.2)
	dt-aiNet	5.86∗10^−11 (1.25∗10^−11)	1 (0.2)
𝐹4	CLONALG	6.93∗10^1 (3.38∗10^1)	3.6 (2.21)
	opt-aiNet	4.57∗10^−5 (4.32∗10^−5)	5.8 (2.2)
	dopt-aiNet	1.03∗10^−1 (5.81∗10^−1)	3.69 (1.3)
	dt-aiNet	1.2∗10^−9 (1.03∗10^−9)	82.54 (8.22)
𝐹9	CLONALG	2.12∗10^0 (4.58∗10^0)	45.6 (20.28)
	opt-aiNet	3.99∗10^−5 (2.47∗10^−5)	60.11 (23.87)
	dopt-aiNet	6.87∗10^−1 (3.9∗10^−1)	32.09 (12.7)
	dt-aiNet	1.68∗10^−11 (1.06∗10^−11)	7.22 (0.43)
𝐹12	CLONALG	7.56∗10^1 (4.35∗10^1)	4.6 (3.10)
	opt-aiNet	5.01∗10^−2 (2.23∗10^−2)	5 (1.43)
	dopt-aiNet	7.61∗10^−1 (5.84∗10^−1)	8.67 (1.33)