The DPSO method and the HDE method rank second and third.
On the part of computational time and convergence, IFA, DPSO, and HDE perform better than FA.
Moreover, the proposed method shows better performance than the DPSO method, HDE method, and FA method.
DPSO Population size 15 Maximum number of iterations 100 Cognitive coefficient 1.
Informap and DPSO first show their weakness, and their detection ability decreases rapidly from [mu] = 0.
As seen from them, DPSO almost gets the same NMI values when [lambda] ranges from 0.
In order to discuss the convergence of the nature inspired algorithms (the proposed algorithm, DPSO, and GA-net algorithm), we choose GN extended benchmark networks [mu] = 0.
As is shown in Figure 6, the proposed algorithm and DPSO have a better performance than the other 4 algorithms on LFR networks because the proposed algorithm and DPSO share the same objective function.
We can see that DPSO and the proposed algorithm have comparative time cost, but GA-net is the most time-consuming since the time complexity of decoding step is more than that of the others.
Only DPSO and the proposed algorithm are considered on the three real-world signed networks because of the limitation of objective functions in the other algorithms.